Agent Architectures

A new approach to software design based on an agent-oriented architecture is presented. Unlike current research, we consider software to be designed and implemented with this methodology in mind. In this approach agents are considered adaptively communicating concurrent modules which are divided into a white box module responsible for the communications and learning, and a black box which is the independent specialized processes of the agent. A distributed Learning policy is also introduced for adaptability. Topics: Agent Architectures, Agents Theories.

Digital twin technology involves creating a high-fidelity virtual replica of a physical system-in this case, spacecraft or entire mission profiles. These virtual models allow engineers to simulate every intricacy of a mission before a single component is built or a launch executed. For example, by modeling a spacecraft in real time, engineers can test how it will respond to the stresses of launch, orbital maneuvers, and even unexpected anomalies such as system failures or environmental disturbances. This simulation capability not only identifies potential issues well before they can cause real-world problems but also enables iterative design improvements at a pace that far outstrips traditional methods. The benefits are profound: Predictive Maintenance: Digital twins allow real-time monitoring and diagnosis, meaning that anomalies can be detected early and corrective actions planned during the mission. Scenario Analysis: Engineers can simulate a variety of mission scenarios-including worst-case conditions-without any risk to the actual spacecraft. Optimized Design: By experimenting in a virtual environment, every component can be refined for maximum efficiency and performance, reducing risks and saving both time and resources in the process. This digital simulation approach dramatically enhances the safety and reliability of mission planning, ensuring that every facet of a mission is scrutinized under multiple simulated conditions before the actual event. Additive Manufacturing: Revolutionizing Component Fabrication Additive manufacturing-commonly known as 3D printing-is radically transforming how spacecraft parts are designed, produced, and integrated. Unlike traditional manufacturing processes that often involve cutting away material, additive manufacturing builds components layer by layer. This not only minimizes material wastage but also allows the creation of highly complex geometries that are impossible to achieve with conventional methods. Key impacts include: Rapid Prototyping: Engineers can design, print, and test prototype components far more quickly, iterating through design improvements in a fraction of the time.

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.

In this work we present a BDI agent architecture used for high level reasoning agents that control mobile robots that play soccer. This architecture is build on top of layered system, where each of these layers is associated with a different level of abstraction. The proposed approach allows the specification of declarative goal driven robot behavior, that uses sophisticated high level reasoning and reactivity when needed. The elements of mental components are studied with their interaction and their syntaxis and semantics are defined.

Planning is commonly viewed as a task to devise a course of action or a plan that conforms as much as possible to a set of goals before acting. The plan will then be used to guide the activities. Most classic planning systems assume a static environment for the planning agents. In a static environment, states remain unchanged between actions, and the outcomes of actions are assumed to be deterministic. In reality, however, most applications are dynamic and stochastic in nature. External events, not caused by controlled actions, may occur; outcomes of actions may differ from expectations; new constraints may be introduced; and a new set of goals may evolve in response to the changes. Recently, we have proposed a multi-modal framework for adaptive planning in a dynamic environment with multiple objectives having the following characteristics: some of the objectives of the planning process may be conflictinḡ some objectives may be ill-defined or difficult to measure quantitativelȳ the objectives may change over time

Intelligent agents and multiagent systems (MAS) provide a scalable approach to distributed artificial intelligence . Analogous to intelligent biological entities, agent-based computational systems may become quite complex. Some may consist of multiple cooperating groups, each providing a specialized subset of the total required functionality . My work focuses on engineering multigroup agents in cooperative intelligent systems. A reusable multigroup agent architecture has been developed, along with a simulation framework and recommended software engineering practices, to support the implementation of multigroup applications. The architecture is being used to evaluate power quality control algorithms for electrical power distribution systems (PDS).

The Procedural Reasoning System (PRS) is the best established agent architecture currently available. It has been deployed in many major industrial applications, ranging from fault diagnosis on the space shuttle to air traffic management and business process control. The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency. Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems. This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects. Our aim in this paper is to rectify this omission. We provide an abstract formal model of an idealised dMARS system (the most recent implementation of the PRS architecture), which precisely defines the key data structures present within the architecture and the operations that manipulate these structures. We focus in particular on dMARS plans, since these are the key tool for programming dMARS agents. The specification we present will enable other implementations of PRS to be easily developed, and will serve as a benchmark against which future architectural enhancements can be evaluated.

The Procedural Reasoning System (PRS) is the best established agent architecture currently available. It has been deployed in many major industrial applications, ranging from fault diagnosis on the space shuttle to air traffic management and business process control. The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency. Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems. This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects. Our aim in this paper is to rectify this omission. We provide an abstract formal model of an idealised dMARS system (the most recent implementation of the PRS architecture), which precisely defines the key data structures present within the architecture and the operations that manipulate these structures. We focus in particular on dMARS plans, since these are the key tool for programming dMARS agents. The specification we present will enable other implementations of PRS to be easily developed, and will serve as a benchmark against which future architectural enhancements can be evaluated.

Production systems must be able to adapt to increasingly frequent internal and external changes. Cyber-Physical Production Systems (CPPS), thanks to their potential capacity for self-reconfiguration, can cope with this need for adaptation. To implement the self-reconfiguration functionality in economical and safe conditions, CPPS must have appropriate tools and contextualized information. This information can be organized in the form of an architecture. In this paper, after the analysis of several holonic and nonholonic architectures, we propose a holonic architecture that allows for reliable and efficient reconfiguration. We call this architecture QHAR (Q-Holonic-based ARchitecture). QHAR is constructed based on the idea of a Q-holon, which has four dimensions (physical, cyber, human, and energy) and can exchange three flows (energy, data, and materials). It is a generic Holon that can represent any entity or actor of the supply chain. The QHAR is structured in three levels: centra...

BDI reasoning mechanism is a well known AI inference approach. Even so, its use in solving the deliberative phase of holonic agents within Holonic Manufacturing Execution Systems still raises open problems. This paper presents the main issues on applying the BDI mechanism in a new holonic structure named HAPBA, which is an instantiation of PROSA reference architecture. The appropriate Petri net models are presented, allowing the analysis of the holonic scheme performance.

This paper presents Intelligent Travel Planning (ITP), a multiagent planning system to solve Web electronic problems in the Web, whose main goal is to search for useful solutions in the electronic-Tourism domain to system users. The system uses different types of intelligent autonomous agents whose main characteristics are cooperation, negotiation, learning, planning and knowledge sharing. Obviously the information used by

Organizational models and holonic multiagent systems are growing as a powerful tool for modeling and developing large-scale complex system. The main issue in deploying holonic multiagent systems is the building of the holonic model called holarchy. This paper presents a novel top down approach based on graph theory in order to build recursively the initial holarchy of road traffic. Moreover, multilevel indicators based on standard deviation is proposed to evaluate the consistency of the holonification process.

Planning and scheduling is the area of artificial intelligence research that focuses on the determination of a series of operations to achieve some set of (possibly) interacting goals and the placement of those operations in a timeline that allows them to be accomplished given available resources. Work in this area at the NASA Ames Research Center ranging from basic research in constrain-based reasoning and machine learning, to the development of efficient scheduling tools, to the application of such tools to complex agency problems is described.

NASA has recently announced the New Millennium Program NMP to develop faster, better, cheaper" spacecraft in order to establish a virtual presence" in space. A crucial element i n a c hieving this vision is onboard spacecraft autonomy, requiring us to automate functions which h a v e traditionally been achieved on ground by humans. These include planning activities, sequencing spacecraft actions, tracking spacecraft state, ensuring correct functioning, recovering in cases of failure and recon guring hardware. In response to these challenging requirements, we analyzed the spacecraft domain to determine its unique properties and developed an architecture which provided the required functionality. This architecture integrates traditional real-time monitoring and control with constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and recon guration. In a ve month e ort we successfully demonstrated this implemented architecture in the context of an autonomous insertion of a simulated spacecraft into orbit around Saturn, trading o science and engineering goals, and achieving the mission goals in the face of any single point of hardware failure. This scenario turned out to be among the most complex handled by each of the component technologies. As a result of this success, the integrated architecture has been selected to control the rst NMP ight, Deep Space One, in 1998. It will be the rst AI system to autonomously control an actual spacecraft.

The Swift programming language is rapidly rising in popularity but it lacks the facilities for true concurrent programming. In this paper we describe an extension to the language which enables access to said concurrent capabilities and provides an api for supporting such interactions. We adopt the ACTOR model of concurrent computation and show how it can be successfully incorporated into the language. We discuss early findings on our prototype implementation and show its usage via an appropriate example. This work also suggests a general design pattern for the implementation of the ACTOR model in the Swift programming language.

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.

Nowadays, session initiation protocol (SIP) is the most important application layer protocol for multi-media to create, modify, and terminate the sessions. SIP is the platform of next generation networks. In this way, SIP should be able to respond to the needs of such a largely-used network. One of the major problems in SIP networks is overload. The basic mechanism embedded in SIP cannot appropriately resolve the due problem by purely rejecting requests, which may cause collapse in network. Many methods have been proposed to overcome overload in SIP, among which, multiagent systems are new agent-based and increasingly growing approaches. Multi-agent system is a powerful tool to model and develop the complex large scale distributed systems. In SIP network, each agent may point out to a server which is in interaction with the others. As a result, a distributed and complex system is simply modeled. The due complexity can be reduced by holonic organization. In this paper, SIP network is divided into geographical areas in which each holon controls an area. The entire network is controlled in hierarchical structure of holons. Holonics structure can be dynamically changed based on the circumstances parameters and the status of the network during execution. Holons implement an end-to-end window-based method. This method offers an appropriate window size for edge servers to control load from the beginning of the network and prevent network overload. The simulation results confirm improved throughput, as well as better reduced call setup delay, rapid response to change and fairness.

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.

Worldwide systems are increasingly growing into unprecedented complexity levels. This increase of system complexity has to be tackled with new control approaches, where decentralization is playing an important role and particularly the Multi-Agent Systems and Holonic Systems. Despite the benefits of this distribution, new problems arise such as the need for entities coordination. This paper proposes an innovative holonic multi-agent system architecture, named ADACOR 2 , which sets foundation on the already proved ADACOR architecture. This new control architecture is empowered by a two vector selforganization, called behavioural and structural self-organization. This paper describes the structural self-organization vector, particularizing the need for embedding in it learning techniques and nervousness stabilizer. A futuristic test bed, inspired in a real flexible-manufacturing system, is used to demonstrate the benefits of this vector in the architecture.

Identification of Relations between BDI Logic and BDI AgentsBDI (Beliefs, Desires, Intentions) is one of the most popular intelligent agent architectures which was inspired by multi-modal BDI logics. The main idea behind BDI is to implement system's behaviour by specifying it as a set of mental objects. This allows designing systems at a high level of abstraction which come closer to a human-like thinking. Although this architecture has been rapidly developing for about 20 years, its relevance to BDI logic is still arguable. This paper describes the basics of modal logic and main inference algorithms. Main concepts of BDI agents are presented and their relationships with BDI logic are discussed. Finally advantages and disadvantages of implementing BDI interpreter as a theorem prover are discussed.

In this paper we will present Eldi, a mobile robot that has been in operation at the Elder Museum of Science and Technology at Las Palmas de Gran Canaria since December 1999. This is an ongoing project that was organized in three dierent stages of which only the rst one has been accomplished. The initial phase, termed The Player, the second stage, actually under development, has been called "The Cicerone" and in the nal phase, termed The Vagabond, in which Eldi will be allowed to move erratically across the Museum. This paper will focus on the accomplished rst stage to succinctly describe the physical robot and the environment and demos developed. Finally we will summarize some important lessons learnt.

In this work we present a BDI agent architecture used for high level reasoning agents that control mobile robots that play soccer. This architecture is build on top of layered system, where each of these layers is associated with a different level of abstraction. The proposed approach allows the specification of declarative goal driven robot behavior, that uses sophisticated high level reasoning and reactivity when needed. The elements of mental components are studied with their interaction and their syntaxis and semantics are defined.

Current use of e-learning management systems(ELMS) in educational institutions is on the rise. These systems are rapidly increasing in regards to volume. Instructional video is one type of content that is inherently large in volume and sequential in nature in accessing the videos which makes it difficult to manage and retrieve information. There has been extensive research on video information retrieval in the past decade. Existing systems need pre-processing by human intervention, are cost prohibitive, or do not exhibit the natural interaction. In this paper, we propose a framework for information retrieval of instructional video content in an ELMS that utilizes Natural Language Understanding / PROCESSING and an Intelligent Agent in a seamless integrated environment to address the key issues of the existing solutions.

In this work we present a BDI agent architecture used for high level reasoning agents that control mobile robots that play soccer. This architecture is build on top of layered system, where each of these layers is associated with a different level of abstraction. The proposed approach allows the specification of declarative goal driven robot behavior, that uses sophisticated high level reasoning and reactivity when needed. The elements of mental components are studied with their interaction and their syntaxis and semantics are defined.

Nowadays, session initiation protocol (SIP) is the most important application layer protocol for multi-media to create, modify, and terminate the sessions. SIP is the platform of next generation networks. In this way, SIP should be able to respond to the needs of such a largely-used network. One of the major problems in SIP networks is overload. The basic mechanism embedded in SIP cannot appropriately resolve the due problem by purely rejecting requests, which may cause collapse in network. Many methods have been proposed to overcome overload in SIP, among which, multiagent systems are new agent-based and increasingly growing approaches. Multi-agent system is a powerful tool to model and develop the complex large scale distributed systems. In SIP network, each agent may point out to a server which is in interaction with the others. As a result, a distributed and complex system is simply modeled. The due complexity can be reduced by holonic organization. In this paper, SIP network is divided into geographical areas in which each holon controls an area. The entire network is controlled in hierarchical structure of holons. Holonics structure can be dynamically changed based on the circumstances parameters and the status of the network during execution. Holons implement an end-to-end window-based method. This method offers an appropriate window size for edge servers to control load from the beginning of the network and prevent network overload. The simulation results confirm improved throughput, as well as better reduced call setup delay, rapid response to change and fairness.

The paper presents a distributed model for implementing Cyber-Physical Systems aimed at controlling physical entities through the Internet of Things. The model tames the inherent complexity of the task by a recursive notion of modularity which makes each module both a controller and a controlled entity. Modules are arranged along part-whole tree-like hierarchies which collectively constitute the system. The behaviour of each module is strictly local since it has visibility only on its controlled modules, but not on the module which controls it. Each behaviour can be thus checked locally at design time against safety and liveness formulas, which still hold when component holons are composed into more complex ones, thus contributing, without the need of additional checks, to the overall safety and liveness of the final system.

The construction of Smart Grids leads to the main question of what kind of intelligence such grids require and how to build it. Some authors choose an agent based solution to realize this intelligence. However, there may be some misunderstandings in the way this technology is being applied. This paper exposes some considerations of this subject, focusing on the Microgrid level, and shows a practical example through INGENIAS methodology, which is a methodology for the development of Agent Oriented systems that applies Model Driven Development techniques to produce fully functional Multi-Agent Systems.

The construction of Smart Grids leads to the main question of what kind of intelligence such grids require and how to build it. Some authors choose an agent based solution to realize this intelligence. However, there may be some misunderstandings in the way this technology is being applied. This paper exposes some considerations of this subject, focusing on the Microgrid level, and shows a practical example through INGENIAS methodology, which is a methodology for the development of Agent Oriented systems that applies Model Driven Development techniques to produce fully functional Multi-Agent Systems.

A trend in regulatory compliance is to issue 'open norms': norms which leave room for contextual interpretation about their implementation. Subjects must demonstrate to the regulator how they have interpreted the norms and collect evidence to show that the implementation is operationally effective. Subjects communicate frequently about the interpretation of open norms and copy compliance behaviour of others. We view this social norm interpretation process as a form of norm emergence. We have performed a case study of adoption of AEO (Authorized Economic Operator) legislation in the EU customs domain. We make two observations: (1) norm adoption is guided in a topdown fashion, by EU guidelines and auditing standards, (2) consensus about what counts as acceptable is reached by interaction among companies, consultants, and auditors. In this paper we review of some literature about norm emergence in the multi agent systems field, which can explain these observations. It turns out that we need to combine two kinds of theories: (i) theories about the specification, prescription and implementation of norms (one-to-many, top-down), and (ii) theories about norm adoption, consensus reaching and norm distribution (many-to-many, bottom-up). 1

The construction of Smart Grids leads to the main question of what kind of intelligence such grids require and how to build it. Some authors choose an agent based solution to realize this intelligence. However, there may be some misunderstandings in the way this technology is being applied. This paper exposes some considerations of this subject, focusing on the Microgrid level, and shows a practical example through INGENIAS methodology, which is a methodology for the development of Agent Oriented systems that applies Model Driven Development techniques to produce fully functional Multi-Agent Systems.

Digitalised models can play a key role in the management of building life-cycle. This paper focuses on the challenges connected to the operation phase of buildings, when the adoption of BIM can make information retrieval and management easier and more efficient. More specifically, a BIM-based cyber-physical system for the automated monitoring of buildings during their regular operation is proposed and tested by means of a customised simulator. The system automatically works out key performance indicators based on the overall throughput effectiveness (OTE) metric, assessing both the overall efficiency and the efficiency of every subsystem integrated in the building. Thus, assessments of the contribution of every subsystem to the operation of the building are performed in real-time. In addition, the metric proposed can help manage multi-objective realtime control. The system is self-reconfigurable thanks to the self-similarity assumption of the computational structure that is designed as a holarchy of holonic systems. The first application reported in this paper shows that when intelligence is embedded at both lower and higher levels, it is possible to generate information that is then used to update the digital model, developed as a BIM. As a result, the digital model becomes the mirror of the physical system and stores the actual performances recorded by the building to support facility managers in making decisions.

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.

Abstract: This paper describes the initial integration of a hybrid reasoning system utilizing a continuous domain feature-based detector, Beacon-based Exceptions Analysis for Multimissions (BEAM), and a discrete domain model-based reasoner, Livingstone. BEAM was ...

This paper presents a proposal of a particular agent-oriented language, called TARDIS 1. Actually, the TARDIS is an extension of a functional language Scheme by including primitives for creating and manipulating agents. Our approach is motivated by a desire to bridge the gap between functional and agent-oriented paradigm. The syntax and semantic we developed was intended to be useful for justifying programs transformations for real languages, and for formalizing intuitive arguments and properties used by programmers.

The paper presents a distributed model for implementing Cyber-Physical Systems aimed at controlling physical entities through the Internet of Things. The model tames the inherent complexity of the task by a recursive notion of modularity which makes each module both a controller and a controlled entity. Modules are arranged along part-whole tree-like hierarchies which collectively constitute the system. The behaviour of each module is strictly local since it has visibility only on its controlled modules, but not on the module which controls it. Each behaviour can be thus checked locally at design time against safety and liveness formulas, which still hold when component holons are composed into more complex ones, thus contributing, without the need of additional checks, to the overall safety and liveness of the final system.

A transportation and logistics domain belongs to complex problems domains because there are many geographically distributed companies who may enter or leave the system at any time. Analysis of the great number of publications reveals that although traditional mathematical modelling and simulation techniques still dominate, new approaches start to appear. Agent technologies and multiagent systems emerge into transportation and logistics domain only recently. The paper proposes the developed multiagent based simulation tool for decision support in transportation and logistics domain. The multiagent system consists from clients' agents and logistics companies agents which may participate in four types of auctions, namely, English auction, Dutch auction, First-price sealed-bid auction and Vickrey auction. A client is an auctioneer who is making decision about the best offer of delivering goods. The simulation tool is implemented using Borland C++ Builder and MS Access database.

Digitalised models can play a key role in the management of building life-cycle. This paper focuses on the challenges connected to the operation phase of buildings, when the adoption of BIM can make information retrieval and management easier and more efficient. More specifically, a BIM-based cyber-physical system for the automated monitoring of buildings during their regular operation is proposed and tested by means of a customised simulator. The system automatically works out key performance indicators based on the overall throughput effectiveness (OTE) metric, assessing both the overall efficiency and the efficiency of every subsystem integrated in the building. Thus, assessments of the contribution of every subsystem to the operation of the building are performed in real-time. In addition, the metric proposed can help manage multi-objective realtime control. The system is self-reconfigurable thanks to the self-similarity assumption of the computational structure that is designed as a holarchy of holonic systems. The first application reported in this paper shows that when intelligence is embedded at both lower and higher levels, it is possible to generate information that is then used to update the digital model, developed as a BIM. As a result, the digital model becomes the mirror of the physical system and stores the actual performances recorded by the building to support facility managers in making decisions.

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.

This paper advocates the application of multi-agent techniques in the realisation of social robotic behaviour. We present an architecture which commissions agent-based deliberation without sacrificing the reactive qualities necessary in a real world domain, and which is situated within a social landscape through the use of an Agent Communication Language.

We describe the incorporation an existing emotion model, the Belief-Desire Theory of Emotion, into the architecture of the agents present in Orphibs II, a Life Simulation videogame prototype. To our knowledge, this represents the first time such a model is employed in video games.

This work aims to bring forward the intersection between the world of statecharts and that of agent technology. We begin by disambiguating the different terms related to statecharts, i.e. state machines and finite state automata / machines. Subsequently we review their impact to agent technology, mainly in the area of Agent-Oriented Software Engineering. Our findings are that multi-agent systems modeling has used and, some times, extended the language of statecharts, mainly for modeling agent interaction protocols and for coordinating the different modules of an agent. We conclude with some future directions related to the use of statecharts by the Multi-agent Systems community in the coming years.

Reproducing daily behaviours requires to be able to schedule behaviours depending on resources and priority constraints. A simple way is to say that behaviours which are using the same resources are mutually exclusive. This approach is not sufficient to obtain realism, as in the real life, humans are able to combine them in a more microscopic way. One way consists in a global specificication of all behaviours in one model, integrating all possible combinations. This solution becomes rapidly too complex and has motivated the work presented in this paper. It consists in an extension of HPTS, our behavioural model which integrates several psychological requirements, by the introduction of resources and priority levels. In the contrary of some previous approaches, it is not necessary to specify exhaustively all behaviours that are mutually exclusive; this is done implicitly by attaching resources to nodes, preference values to transitions, and a priority function to each behaviour, and by using a scheduling algorithm at run-time.

Future energy systems require decentralized regulatory approaches. Aggregates, equipped with appropriate sensors, can behave independently for the purposes of system stability. To explore and evaluate appropriate control mechanisms a multiagent-based simulation will be developed. It enables realistic simulations of electricity grids and decentralized consumption, storage and production units as well as provides the basis for further research whether the concept in scale could be successful. We describe the general architecture of such a simulation approach in comparison to existing literature.

Intelligent agents and multiagent systems (MAS) provide a scalable approach to distributed artificial intelligence [3]. Analogous to intelligent biological entities, agent-based computational systems may become quite complex. Some may consist of multiple cooperating groups, each providing a specialized subset of the total required functionality [4, 6]. My work focuses on engineering multigroup agents in cooperative intelligent systems. A reusable multigroup agent architecture has been developed, along with a simulation framework and recommended software engineering practices, to support the implementation of multigroup applications. The architecture is being used to evaluate power quality control algorithms for electrical power distribution systems (PDS).

Organization-based agents dynamically create, manage, and participate in groups governed by common goals. In complex applications, agents may participate simultaneously in multiple organizations, requiring agents to manage their associations and assignments in a consistent, unambiguous way. The Organization-Based Agent Architecture (OBAA ++ ) explicitly supports multigroup agents and is being used to evaluate a holonic MAS for power quality control.

This paper describes the application of an Organization-based Multiagent System Engineering (O-MaSE) compliant process to the development of a holonic multiagent system (MAS) for testing control algorithms for an intelligent power distribution system. The paper describes the Adaptive O-MaSE (AO-MaSE) process, which provides architects and developers a structured approach for testing and iteratively adding functionality in complex, adaptive systems. The paper describes the holonic MAS architecture for the intelligent power distribution system, the challenges encountered while developing the holonic architecture, the lessons learned during the project, and demonstrates how the application of the process enhanced project development.

This paper describes the validation rocess for the Autonomous Science A ent, a so R ware agent that is currently flying on % oard NASA’s EO-1 spacecraft. The agent autonomously collects, analyzes, and reacts to onboard science data. The Autonomous Science Agent has been designed using a layered architectural ap roach with specific redundant safeguards to re ts uce the risk of an agent malfunction to the EO-1 spacecraft. This “safe ” design has been thoroughly validated by informal validation methods supplemented by sub-system and s stem-level testing. This paper elements of the design that increase the safety of the agent, and the process used to validate agent safety. descnbes the ana Y ysis used to define agent safety,

ABSTRACT: We provide an update on dTank (Morgan et al., BRIMS 2005), a highly usable adversarial environment. It can be used for examining performance variability in situation awareness and architectural comparisons of competitive agents. First, the new design and implementation details of the updated dTank environment are discussed. In-progress models constructed with several cognitive and agent architectures (Java, Jess, and Soar) are then noted. Next, in the moderated behavior section, we present preliminary analyses of embedded performance delays in reaction to battlefield environmental conditions. Noise factors and variability in delay length at the tank commander level lead to different battle outcomes. Finally, we note some changes that will be required for dTank to better model situation awareness. Light-weight agent-construction environments such as dTank fill an important need for experimentation and prototyping tools that support quick scenario development and behavior im...

The paper presents a distributed model for implementing Cyber-Physical Systems aimed at controlling physical entities through the Internet of Things. The model tames the inherent complexity of the task by a recursive notion of modularity which makes each module both a controller and a controlled entity. Modules are arranged along part-whole tree-like hierarchies which collectively constitute the system. The behaviour of each module is strictly local since it has visibility only on its controlled modules, but not on the module which controls it. Each behaviour can be thus checked locally at design time against safety and liveness formulas, which still hold when component holons are composed into more complex ones, thus contributing, without the need of additional checks, to the overall safety and liveness of the final system.