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Title
Abstract
Figures
Introduction
Design Methodologies for (Intelligent) Agents
Designing a Self-Modifying Agent
Discussion
References
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Computer Science
Artificial Intelligence

Designing self-modifying agents

Profile image of Frances BrazierFrances Brazier

2001, … of Computational and Cognitive Models of …

Abstract

Agents need to be able to adapt to changes in their environment. One way to achieve this, is to provide agents with the ability of self-modification. Self-modification requires reflection and strategies with which new knowledge can be acquired, a necessary condition for creativity. This paper describes a knowledge-level model for the design of self-modifying agents and explores the feasibility of automatically designing self-modifying agents. * To appear in Proceedings of the Creative Design Workshop, December 2001. * relate description of agent to properties of agent * relate required properties to required properties * relate required properties to structure modifications of an agent * understand tasks, the ontologies, knowledge, and control involved * make strategic decisions within the agent's own process control * determine which strategies to deploy within an agent * resolve conflicts within an agent and strategies are needed to * guide the overall design process * alternate between viewpoints on design requirements and agent descriptions * prioritize possible strategies for self-modification. The process of designing a self-modifying information retrieval agent, introduced in Section 3.3, is used as an illustration. The self-modifying information retrieval agent was designed on the basis of the following requirements: 1. The agent is able to find information on web-pages. 2. The agent is able to adapt itself. 3. The agent is able to communicate with other agents on queries and query results. These requirements state that the information retrieval agent is able to find information on the web. To design such an agent, the design process needs specific knowledge of * designing an information retrieval agent * self-modification capabilities * reflective capabilities * modification of information retrieval agents.

Figures (3)
Figure 1. Process abstraction levels for a generic co-operative agent.
Figure 1. Process abstraction levels for a generic co-operative agent.
The self-modification process is shown in Figure 2. In this model an initial self-modification problem statement is expressed as a set of initial self- modification requirements and requirement qualifications. Requirements impose conditions and restrictions on the structure, functionality and behaviour of the agent itself for which a structural description is to be modified during self-modification. Qualifications of requirements are qualitative expressions of the extent to which (individual or groups of) self- modification requirements are considered to be hard or preferred, either in isolation or in relation to other (individual or groups of) self-modification requirements. At any one point in time during design, the self-modification process focuses on a specific subset of the set of self-modification requirements. This subset of requirements plays a central role; the design process is (temporarily) committed to the current self-modification requirement qualification set: the aim of generating a design object description is to satisfy these requirements. Figure 2. Process abstraction levels for the process of self-modification.
The self-modification process is shown in Figure 2. In this model an initial self-modification problem statement is expressed as a set of initial self- modification requirements and requirement qualifications. Requirements impose conditions and restrictions on the structure, functionality and behaviour of the agent itself for which a structural description is to be modified during self-modification. Qualifications of requirements are qualitative expressions of the extent to which (individual or groups of) self- modification requirements are considered to be hard or preferred, either in isolation or in relation to other (individual or groups of) self-modification requirements. At any one point in time during design, the self-modification process focuses on a specific subset of the set of self-modification requirements. This subset of requirements plays a central role; the design process is (temporarily) committed to the current self-modification requirement qualification set: the aim of generating a design object description is to satisfy these requirements. Figure 2. Process abstraction levels for the process of self-modification.
Figure 3. Five-stage model of the creative process (taken from Lawson, 1997). Gero’s model for creative design (1996) is based on the view that creativity results from a discrepancy between expectations and unexpected results. If the unexpected results can be understood, then they are considered to be a creative solution. When, however, the unexpected results cannot be understood, these results are rejected as faulty. A self-modification process may have side effects that had not been anticipated. Influences on the creativity of an agent with respect to its own specific task may be purposefully sought by re-design, without knowing the results. In both cases, how well the results are understood will depend on the situation, e.g. who is responsible for monitoring an agent’s behaviour - a human being or another automated agent.
Figure 3. Five-stage model of the creative process (taken from Lawson, 1997). Gero’s model for creative design (1996) is based on the view that creativity results from a discrepancy between expectations and unexpected results. If the unexpected results can be understood, then they are considered to be a creative solution. When, however, the unexpected results cannot be understood, these results are rejected as faulty. A self-modification process may have side effects that had not been anticipated. Influences on the creativity of an agent with respect to its own specific task may be purposefully sought by re-design, without knowing the results. In both cases, how well the results are understood will depend on the situation, e.g. who is responsible for monitoring an agent’s behaviour - a human being or another automated agent.

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This paper presents the design and implementation details of an information retrieval system. A multi-agent architecture has been adopted to allow for extended flexibilities over similar traditional systems. Since the system is consisted of various types of agents a short agent information will be given first. It will also explained that how these agents communicate with each other in order to accomplish information gathering through an agent messaging router which is a part of a software package called JATlite (Java Agent Template). JATLite provides the basic infrastructure for creation of agents and their communication.

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Software agents for information retrieval
James Mayfield

Tutorial at Third ACM Conference on Digital Libraries, Pittsburg, 1998

The advent of large wide-area networks connecting many diverse repositories of data creates the challenge of finding particular data of interest in an easy and timely manner. This paper describes the initial prototype of a system that addresses this problem by using a set of autonomous, customizable software agents. Central to the system design are scripts-arbitrary, parameterized program segments written in a language that contains primitives for interacting with the data environment and tagged with keywords describing their purposes-that define the functionality of an agent. Agents can query the keywords associated with other agents' scripts and can import scripts from one another, thereby providing a mechanism for agents to learn from one another.

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Automated (Re-)Design of Software Agents
Niek Wijngaards, Frances Brazier

Artificial Intelligence in Design ’02, 2002

Autonomous software agents are dynamic entitities: they are capable of discovering a need for change -for additional knowledge and/or functionality on the basis of their analysis of specific situations. Agent factories are capable of redesigning and reactivating agents on the basis of the information provided by agents and/or knowledge available within the agent factories. As a result agents may evolve in ways their designers could never have pre-conceived. The artefacts themselves are dynamic in a way that can not be compared to any other type of design in current design practice. A number of prototype agents and agent factories have been built to evaluate the feasibility of this concept and its consequences.

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  • Engineering
  • Computational Cognitive Models
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