1. peer-to-peer and agent-based computing Agents & Multi-Agent Systems: Introduction (Contd)

2. peer-to-peer and agent-based computing 2 Objection: agents are just objects! Objects: –Encapsulate state –Communicate via message-passing –Have methods corresponding to operations performed on its state Agents: some objections

3. peer-to-peer and agent-based computing 3 Agents: some objections (Contd) Agents, however, have unique characteristics: –They embody a stronger notion of autonomy than objects –They decide for themselves how to respond to a message –They are capable of flexible behaviour reactive, goal-directed social The standard object model has nothing to say about these types of behaviour –They are active A MAS is inherently multi-threaded – each agent is assumed to have at least one thread of control

4. peer-to-peer and agent-based computing 4 Agents vs. objects Agents initiate actions on their own, objects dont Agents are aware of their environment, objects arent If requested, –Objects do it because they have to, –Agents do it if they decide to… Agents: some objections (Contd)

5. peer-to-peer and agent-based computing 5 Agents: some objections (Contd) Objection: agents are just a re-branding of expert systems. Expert systems encapsulate disembodied expertise about some domain Agents are: – Situated in an environment, and – Act on that environment. However, some real-time (e.g. process control) expert systems are agents…

6. peer-to-peer and agent-based computing 6 Is it all AI, then? Agents have enjoyed a close relationship with AI, but they are different (intersecting) fields Distributed AI: –Intelligence emerging from teams of experts –Distributed problem-solving Agents embody and integrate different kinds of intelligence: –Planning, reasoning, search, learning, etc. No need to solve all of AI to program agents: –A little intelligence goes a long way… Agents: some objections (Contd)

7. peer-to-peer and agent-based computing 7 Environments can be: Accessible –agents can obtain complete, accurate and up-to-date information about the state of the environment. –The more accessible an environment is, the simpler it is to build agents to operate in it. –As an environment becomes more complex, it becomes less accessible Deterministic –Actions have guaranteed and predictable effects. –In other words, there is no uncertainty about the state of the world that will result from performing an action. –Non-deterministic environments pose greater challenge to agents design –The physical world can be regarded as non-deterministic (even if we assume that the physics of the environment can be reliably modeled). Characteristics of environments

8. peer-to-peer and agent-based computing 8 Environments can be: Static: –Change only due to the agents actions and the effects of the actions are stable. Dynamic: –Other agents actions or entropy may change it. Discrete: –There are a fixed and finite number of possible states. Continuous: –There are infinite possible states. –A chess game is a discrete environment and taxi driving is a continuous environment. Environments (Contd)

9. peer-to-peer and agent-based computing 9 Agents are systems/programs that –Perceive their environment through sensors –Act upon the environment through actuators –Sensors: Cameras, keystrokes, streams arriving in sockets, etc. –Actuators: Variable, web page, database entry, robot arm, etc. Inside agents Environment Agent Sensors Actuators ? Percepts Actions

10. peer-to-peer and agent-based computing 10 Percept: –The agents perceptual inputs at a given instant –What the agent makes of the environment –Percept sequence is the history of what the agent has perceived so far. –An agents choice of action can depend on the entire percept sequence observed to date. An agent function uniquely defines the behaviour: –We can provide the same effect with a program! Inside agents (Contd) f( p 1,…,p n ) = action 1 f( q 1,…,q m ) = action 2 …

11. peer-to-peer and agent-based computing 11 Simple reflex agent –Takes action based on current percept Agent programs Environment Percepts Actions Agent Sensors Actuators What the world is like now What action I should do now Condition-action rules

12. peer-to-peer and agent-based computing 12 Model-based reflex agent –Uses model of the world to make up for incomplete info Agent programs (Contd) Environment Percepts Actions Agent Sensors Actuators What the world is like now What action I should do now Condition-action rules State How the world evolves What my actions do

13. peer-to-peer and agent-based computing 13 Model-based utility-based agent –Uses utility function to choose among possible actions Agent programs (Contd) Environment Percepts Actions Agent Sensors Actuators What the world is like now What action I should do now Utility State How the world evolves What my actions do What it will be like if I do action A How happy I will be in such a state

14. peer-to-peer and agent-based computing 14 The Intentional Stance Daniel Dennett coined the term intentional system to describe entities: –whose behaviour can be predicted by the method of attributing belief, desires and rational acumen When explaining human behaviour, it is useful to make statements such as: –John enrolled in the course because he believed that a degree would help him get a better job –Sue worked hard because she wanted to graduate Daniel Dennett

15. peer-to-peer and agent-based computing 15 Intentions for Machines? To ascribe beliefs, free will, intentions, consciousness, abilities or wants to a machine is legitimate when such an ascription expresses the same information about the machine that it expresses about a person It is useful when the ascription helps us to understand the structure of the machine, its past or future behaviour, or how to repair or improve it. It is perhaps never logically required even for humans, but expressing reasonably briefly what is actually known about the state of the machine in a particular situation may require mental qualities or qualities isomorphic to them. Theories of belief, knowledge and wanting can be constructed for machines in a simpler setting than for humans. Ascription of mental qualities is most straightforward for machines of known structure such as thermostats and computer operating systems, but is most useful when applied to entities whose structure is incompletely known. John McCarthy

16. peer-to-peer and agent-based computing 16 The Intentional Stance (cont.) What objects can be described by the intentional stance? It is perfectly coherent to treat a light switch as a (very co-operative) agent with the capability of transmitting current at will, who invariably transmits current when it believes that we want it transmitted and not otherwise; flicking the switch is simply our way of communicating our desires Yoav Shoham This is absurd, but why? … it does not buy us anything, as we understand the mechanism sufficiently to have a simpler, mechanistic description of its behaviour.

17. peer-to-peer and agent-based computing 17 Intentional Stance as an Abstraction A mechanistic explanation of the behaviour of a very complex system may not be practical As computer systems become more complex, we need more powerful abstractions and metaphors to explain their behaviour In computing, abstractions are important: –The procedural abstraction –Abstract data types –Objects –Agents as intentional systems

18. peer-to-peer and agent-based computing 18 Intentional Stance: Advantages It provides us with a familiar, non-technical way of understanding and explaining agents without the need to understand the underlying mechanism. It gives us the potential to specify systems that include representations of other systems. It allows us to give a very abstract specification and leave it to the control mechanism, based on a theory of agency, to determine what to do.

19. peer-to-peer and agent-based computing 19 Intentional Stance: Limitations When modelling communication: –If Bob says Computers are the root of all evil –What can we say about Bobs psychological state as a result of him saying this? –Can we say Bob believes it? Can we say that we believe that Bob believes it? When modelling organisations: –Compare every lecturer intends to attend the staff meeting with every lecturer ought to attend the staff meeting

20. peer-to-peer and agent-based computing 20 Reading List An Introduction to Multi-Agent Systems, M. Wooldridge, John Wiley & Sons, 2008 Is it an agent or just a program? S. Franklin and A. Graesser, available on-line at http://www.msci.memphis.edu/~franklin/AgentProg.html Artificial Intelligence: A Modern Approach (2 nd Ed.), S. Russell and P. Norvig, Prentice-Hall, 2003 Multi-Agent Systems: A Modern Approach to Distributed Artificial Intelligence, G. Weiss (editor), MIT Press, 1999 Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, J. Ferber, Addison- Wesley, 1999