I've decided to publish some of the theoretical material I've surveyed... here is the first part.
What are intelligent agents
Agents are loosely defined as being a computer based system characterized by their autonomy (no direct human intervention required), their social ability allowing them to communicate with other agents or human, their reactivity allowing them to react to the changing environment and finally their pro-activeness which also permit them to take initiative to meet their goal. In fact the key characteristics of reactivity, pro-activeness and social ability can be considered as main differentiator between “normal” agent and “intelligent” agent.
Other more formal definition would also include some human alike concepts such as knowledge, belief, intention and obligation, as well as additional properties like mobility, veracity, benevolence and rationality.
An important aspect of agent has to do with their surrounding environment which they operate in. To see the impact of environmental properties on agent, one can classify them as being:
Accessible/inaccessible: accessible environment would be one for which all states are known up-to-date and accurately. In all practical cases, the environment is inaccessible, e.g. surrounding physical world, Internet, etc.
Deterministic/non-deterministic: except for the most trivial case, agents has only partial and non-deterministic control over their environment are, i.e. same action performed twice on seemingly identical circumstances may appear to have different consequences. Although non-deterministic lead to more complex system, to all intents and purposes it is recognized that a highly complex deterministic environment is just as difficult as a non-deterministic.
Episodic/non-episodic: episodic system has performance dependant only on the current discrete episode. This simplifies design since all possible scenarios and interaction in future episodes can be ignored in relation to deciding which actions are to be taken by the agents.
Static/dynamic: static environment only observe changes in reaction to action performed by the agent, in most situation other unknown/known processes operate on the environment making it dynamic.
Discrete/continuous: Discrete environment implies only a finite number of actions and percept to be possible.
It is recognised that with respect to building agent, most complex class of environment are those that are inaccessible, non-deterministic, non-episodic, dynamic and continuous.
Agent theory
A substantial part of agent theories are derived around the concept of intentional system, i.e. system with behaviour that are predicted based on similar human type attitudes: belief and knowledge (referred to as information category), and desire, intention, obligation, commitment and choice (referred to as pro-attitudes). Following this concept, merely all objects from the most simples automata-like objects to the most complex ones, can be described by having some form of intentional stance. This fact helps to provide a level of abstraction useful when dealing with the complexity of the latter.
As “compelling” as the intentional notions are for an intuitive representation, description, understanding and explanation of agent based system, it can certainly represent a difficult challenge when one wishes to reason about this inside a logical theoretical framework. Theory for representing intentional notion cannot be based using classical relying on truth functional operator, because this notion is said to be referential opaque. Substitution rule applicable to first order logic are not possible with intentional sentence such as “Janine believes p”, since replacing p with an equivalent will not preserve meaning.
Because of this limitation, other formalisms have been proposed for handling the syntactic rules and the semantic model associated with intentional system. One of the best known semantic model is characterized by the so-called “possible worlds” which is supported by an attractive mathematical tools called the “correspondence theory”. However as compelling as this model is for its logic representation, it suffers from limitations related to the famous “logical omniscience” (see problem due to infinite knowledge caused by statement logical tautology). In this 1995 study, the authors recognized that alternatives theories developed for either belief/knowledge representation (information attitudes) or goals/desire (pro-attitudes) all suffer from various deficiencies and/or limitations representing challenges to the agent theorist.
A more useful and complete theory for agent system should not only try representing the intentional stance but should also try embracing a larger logical framework interested in other components such as the dynamic aspects of agency, the relationship between the agent’s information and its pro-attitudes, the cognitive states change over time and reaction to the environment stimuli, etc. Some tentative work aims to achieve this very challenging task.
Of particular interest is communication between agents, which are modelled using the “speech act theory” stating that all communications are considered as actions performed to bring change to the world (usually to the listener internal state). This theory attempts to classify between the various forms of speech acts, with the two prominent ones being representative speech act for informing objectives and the directives one for requesting objective. See Multiagents system discussion below.
Taken from
“Intelligent Agents: Theory and Practice”, Wooldridge and Jennings (1995)
“Multiagent Systems, a Modern Approach to Distributed Modern Approach to Artifical Intelligence” Chapter 1 Intelligent Agents, Wooldridge (1999)
Posts
No comments:
Post a Comment