Computer and Information Science

A search on Google for the keywords "intelligent agents" will return more than 330,000 hits; "multi-agent" returns almost double that amount. Over 5,000 citations appear on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as:

Recently, a prototype relational database system has been developed that has the capability of storing and querying analog and video information for interaction with data analysis applications . The system provides for numerous querying categories via indexed meta-data using pre-filled, drop-own combo boxes. A shortcoming of the design is the growing number of categories that could in time become unmanageable. One purpose of this study was to explore a more flexible design that would reduce the number of categories for storing and querying the database. In this design, the user enters a compound, logical query statement with the desired keywords in addition to using the existing combo boxes. This proved to be a more efficient and flexible strategy for accommodating expanding search categories. Another purpose of this study was to add security features in accessing database information to restrict sharing of information about subject populations. This has become an important requirement in accessing subject information in research studies. To this end we have developed an easily reusable security hierarchy in which individual users and groups of users can be granted rights to objects of the system e.g., database tables or user interface tabs. The permissions granted to a user are dynamically updated by group permissions as the user joins or leaves these groups. The initial implementation of security features has proven to be efficiently handled by the interface. Thus, a prototype for a flexible and secure database querying capability has been implemented that can be scaled to meet the expanding needs of researchers.

This paper describes work from the Bridges to Computing project at Brooklyn College of the City University of New York. This project focuses on the transition from high school to college with the intention of encouraging more students to study some aspect of computer science. The Bridges project has both introduced new undergraduate courses into our computer science curriculum and revised existing courses, as well as developed activities for high school students to help better prepare them for college-level computer science. Here, we report on the use of ideas from artificial intelligence implemented within several of these interventions.

A prototype relational database system was developed that has indexing capability, which threads into data acquisition and analysis programs used by a wide range of researchers. To streamline the user interface and table design, free-formatted table entries were used as descriptors for experiments. This approach potentially could increase data entry errors, compromising system index and retrieval capabilities. A methodology of integrating intelligent agents with the relational database was developed to cleanse and improve the data quality for search and retrieval. An intelligent agent was designed using JACK TM (Agent Oriented Software Group) and integrated with an Oracle-based relational database. The system was tested by triggering agent corrective measures and was found to improve the quality of the data entries. Wider testing protocols and metrics for assessing its performance are subjects for future studies. This methodology for designing intelligent-based database systems should be useful in developing robust largescale database systems.

Abstract Studies of neural function that are carried out in different laboratories and that address different questions use a wide range of descriptors for data storage, depending on the laboratory and the individuals that input the data. A common approach to describe non-textual data that are referenced through a relational database is to use metadata descriptors. We have recently designed such a prototype system, but to maintain efficiency and a manageable metadata table, free formatted fields were designed as table entries.

Research in computational neuroscience has been following a model-based approach where data is comprised of digitized streams of sampled analog data, images and voice. The data are generally contained in files and specialized programs are used to analyze the data. In this study we developed a prototype system for indexing and retrieving information for use by an application that analyzes data. The data in the files consist of channels derived from analog and event driven sources. It is also linked to video images associated with the data acquisition. In this research, we developed an indexing capability that threads into the data acquisition and analysis programs to give the system a broad data base capability. We designed tables and relations within the database for indexing the files and information contained within the file. The system has the potential of giving us retrieval capabilities that include analog, event, and video data types.

Studies of neural function that are carried out in different laboratories and that address different questions use a wide range of descriptors for data storage, depending on the laboratory and the individuals that input the data. A common approach to describe non-textual data that are referenced through a relational database is to use metadata descriptors. We have recently designed such a prototype system, but to maintain efficiency and a manageable metadata table, free formatted fields were designed as table entries. The Database Interface Application utilizes an intelligent agent to improve integrity of operation. The purpose of this study was to investigate how reinforcement learning algorithms can assist the user in interacting with the Database Interface Application that has been developed to improve the performance of the system.

In an effort to broaden participation in computing, the authors have initiated a series of interventions focusing on the recruitment, preparation, and retention of under-represented students in computer science. Their approach is to emphasize the practical side of computing through a series of tracks: business, law, medicine, graphics and multimedia, and robotics and simulation. This paper describes one of those interventions: a summer institute, conducted in 2006, that gives local high school students a taste of what computing is all about.

Recently, a prototype relational database system has been developed that has the capability of storing and querying analog and video information for interaction with data analysis applications [8]. The system provides for numerous querying categories via indexed meta-data using pre-filled, drop-own combo boxes. A shortcoming of the design is the growing number of categories that could in time become unmanageable. One purpose of this study was to explore a more flexible design that would reduce the number of categories for storing and querying the database. In this design, the user enters a compound, logical query statement with the desired keywords in addition to using the existing combo boxes. This proved to be a more efficient and flexible strategy for accommodating expanding search categories. Another purpose of this study was to add security features in accessing database information to restrict sharing of information about subject populations. This has become an important requi...

This paper describes work from the Bridges to Computing project at Brooklyn College of the City University of New York. This project focuses on the transition from high school to college with the intention of encouraging more students to study some aspect of computer science. The Bridges project has both introduced new undergraduate courses into our computer science curriculum and revised existing courses, as well as developed activities for high school students to help better prepare them for college-level computer science. Here, we report on the use of ideas from artificial intelligence implemented within several of these interventions.

In an effort to broaden participation in computing, the authors have initiated a series of interventions focusing on the recruitment, preparation, and retention of under-represented students in computer science. Their approach is to emphasize the practical side of computing through a series of tracks: business, law, medicine, graphics and multimedia, and robotics and simulation. This paper describes one of those interventions: a summer institute, conducted in 2006, that gives local high school students a taste of what computing is all about.

A prototype relational database system was developed that has indexing capability, which threads into data acquisition and analysis programs used by a wide range of researchers. To streamline the user interface and table design, free-formatted table entries were used as descriptors for experiments. This approach potentially could increase data entry errors, compromising system index and retrieval capabilities. A methodology of integrating intelligent agents with the relational database was developed to cleanse and improve the data quality for search and retrieval. An intelligent agent was designed using JACKTM (Agent Oriented Software Group) and integrated with an Oracle-based relational database. The system was tested by triggering agent corrective measures and was found to improve the quality of the data entries. Wider testing protocols and metrics for assessing its performance are subjects for future studies. This methodology for designing intelligent-based database systems shoul...

Recently, a prototype relational database system has been developed that has the capability of storing and querying analog and video information for interaction with data analysis applications [8]. The system provides for numerous querying categories via indexed meta-data using pre-filled, drop-own combo boxes. A shortcoming of the design is the growing number of categories that could in time become unmanageable. One purpose of this study was to explore a more flexible design that would reduce the number of categories for storing and querying the database. In this design, the user enters a compound, logical query statement with the desired keywords in addition to using the existing combo boxes. This proved to be a more efficient and flexible strategy for accommodating expanding search categories. Another purpose of this study was to add security features in accessing database information to restrict sharing of information about subject populations. This has become an important requi...

Abstract- Research in computational neuroscience has been following a model-based approach where data is comprised of digitized streams of sampled analog data, images and voice. The data are generally contained in files and specialized programs are used to analyze the data. In this study we developed a prototype system for indexing and retrieving information for use by an application that analyzes data. The data in the files consist of channels derived from analog and event driven sources. It is also linked to video images associated with the data acquisition. In this research, we developed an indexing capability that threads into the data acquisition and analysis programs to give the system a broad data base capability. We designed tables and relations within the database for indexing the files and information contained within the file. The system has the potential of giving us retrieval capabilities that include analog, event, and video data types. I.

double that amount as well as over 5,000 citations on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and agent usage are discussed.

A search on Google for the keywords "intelligent agents" will return more than 330,000 hits; "multi-agent" returns almost double that amount. Over 5,000 citations appear on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and agent usage are discussed.

A search on Google for the keywords “intelligent agents ” will return more than 330,000 hits; “multi-agent ” returns almost double that amount. Over 5,000 citations appear on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and...

We explore AI-based methods for analyzing and visualizing data collected from on-line assessments of young students' numeracy and literacy skills. Traditionally, educational assessment data is reported in the form of test scores, often two numbers that each represent a student's achievement or ability in mathematics and language. However, state-of-the-art, adaptive on-line environments are gaining favor for student assessment and these types of systems obtain a wealth of data. Distilling these robust data sets down to two numbers results in great loss of information; and we have been exploring richer ways of presenting and analyzing these data to allow deeper understanding of student performance by teachers, parents and education researchers.