1. NAVEEN AGENT BASED SOFTWARE DEVELOPMENT

2. WHAT IS AN AGENT? A computer system capable of flexible, autonomous (problem-solving) action, situated in dynamic, open, unpredictable and typically multi-agent domains. reactive: respond in timely fashion to environmental change proactive: act in anticipation of future goals

3. MULTIPLE AGENTS In most cases, single agent is insufficient no such thing as a single agent system (!?) multiple agents are the norm, to represent: natural decentralisation multiple loci of control multiple perspectives competing interests

4. AGENT BASED COMPUTING Modern computing is defined by the interconnection of computers The World Wide Web now provides a basic infrastructure for dynamic provision of online services The information society arises from the use of distributed, dynamic and open systems across all aspects of everyday life Computers are in embedded devices, support systems as well as the traditional desktop

5. AGENTS AS SIMULATION Multi-agent systems offer strong models for representing complex and dynamic real-world environments. For example, simulation of economies, societies and biological environments are typical application areas.

6. DYNAMIC AND OPEN ENVIRONMENTS Networked computers Dynamic interactions to form new system configurations Enable increased flexibility May span organizational boundaries Can operate in rapidly changing circumstances with changing information Traditional models of computation are inadequate

7. AUTONOMY Need to respond dynamically to changing circumstances while trying to achieve overarching objectives without user intervention Web Services, for example offer new ways of operating through standardized tools support a service-oriented view of software Agent technologies offer a way to tackle the problems and manage the resulting complexity

8. AGENT-BASED SYSTEMS Agent-based systems have emerged from a convergence of technologies in Distributed object systems Distributed artificial intelligence Agent technologies are already providing benefits in, for example, Manufacturing Supply chain management B2B exchanges

9. AGENTS VERSUS OBJECTS Like objects, agents encapsulate state and behaviour But objects are essentially passive They have no choice over interaction They are invoked by other objects Agents decide whether to perform the desired operation Agents are autonomous

10. Objects provide a valuable way to model the world But agents provide a more natural representation of real-world systems in which different individuals interact according to their own agendas and priorities. They can come together to achieve overarching objectives that might not, or not as easily, be achieved by the individuals alone

11. MICRO AND MACRO ISSUES If one aims to build a computer system such as that indicated in the example scenario, then there are at least two sorts of issues that one needs to address Micro-issues. How does one build an agent that has the kind of properties listed above? This is the area that has become known as agent architectures. Macro-issues. How does one design an agent society that can (co-)operate effectively? This latter area has been the primary focus of research in Distributed AI (DAI)

12. AGENT PROGRAMMING LANGUAGES Most research in agent-oriented programming languages is based on declarative approaches, mostly logic based. Imperative languages are in essence inappropriate for expressing the high-level abstractions associated with agent systems design; however, agent-oriented programming languages should (and indeed tend to) allow for easy integration with (legacy) code written in imperative languages. From the technological perspective, the design and development of agent-based anguages is also important.

13. AGENT PROPERTIES Learning ability Adaptability Mobility Veracity Mobility Benevolence Rationality Temporal continuity Believable personality communication ability

14. AGENTLINK GOALS Competitive advantage through promotion of agent systems technology Improvement in standard, profile, industrial relevance of research in agents Promote excellence of teaching and training High quality forum for R&D

15. AGENTS AS DESIGN Agent oriented software engineering Agent architectures Mobile agents Agent infrastructure Electronic institutions

16. AGENT TECHNOLOGIES Multi-agent planning Agent communication languages Coordination mechanisms Matchmaking architectures Information agents and basic ontologies Auction mechanism design Negotiation strategies Learning

17. APPLICATION AND DEPLOYMENT Assistant agents Multi-agent decision systems Multi-agent simulation systems IBM, HP Labs, Siemens, Motorola, BT Lost Wax, Agent Oriented Software, Whitestein, Living Systems, iSOCO