Distributed artificial intelligence

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Distributed artificial intelligence (DAI) was a subfield of Artificial intelligence research dedicated to the development of distributed solutions for complex problems regarded as requiring intelligence. These days DAI has been largely supplanted by the field of Multi-Agent Systems. See the paper by Inman and Hewitt on some of the limitations of classic DAI.

Main streams in DAI research included the following:

  • Parallel problem solving: mainly deals with how classic AI concepts can be modified, so that multiprocessor systems and clusters of computers can be used to speed up calculation.
  • Distributed problem solving (DPS): the concept of agent, autonomous entities that can communicate with each other, was developed to serve as an abstraction for developing DPS systems. See below for further details.
  • Multi-Agent Based Simulation (MABS): a branch of DAI that builds the foundation for simulations that need to analyze not only phenomena at macro level but also at micro level, as it is in many social simulation scenarios.

The key concept used in DPS and MABS is the abstraction called software agents. An agent is a virtual (or physical) autonomous entity that has an understanding of its environment and acts upon it. An agent is usually able to communicate with other agents in the same system to achieve a common goal, that one agent alone could not achieve.

A first classification that is useful is to divide agents into:

  • reactive agent - A reactive agent is not much more than an automata that receives input, processes it and produces an output.
  • deliberative agent - A deliberative agent in contrast should have an own internal view of its environment and is able to follow its own plans.
  • hybrid agent - A hybrid agent at last is a mixture of reactive and deliberative, that follows its own plans, but also sometimes directly reacts to external events without deliberation.

Well recognized agent architectures that describe how an agent is internally structured are:

  • Soar (a rule-based approach)
  • BDI (Believe Desire Intention, a general architecture the describes how plans are made)
  • InterRAP (A three-layer architecture, with a reactive, a deliberative and a social layer)
  • PECS (Physics, Emotion, Cognition, Social, describes how those four parts influences the agents behaviour).

Software agents can communicate with one another using an agent communication language.

The DAI and Multi-Agent Systems (MAS) technologies are especially developed for complex distributed Intelligent Decision Support Systems (IDSS), see for ex. "Towards intelligent decision support systems for emergency managers: the IDA approach", 2001, Intelligent Tutoring Systems (ITS), as well as, for Intelligent e-learning and mobile learning networks.

Important researchers in the area of agents are:

Contents

[edit] See also

collective intelligence

[edit] References

  • Carl Hewitt and Jeff Inman. DAI Betwixt and Between: From "Intelligent Agents" to Open Systems Science IEEE Transactions on Systems, Man, and Cybernetics. Nov./Dec. 1991.

[edit] In Literature

The Michael Crichton novel Prey uses distributed agents heavily in the plot.

[edit] External links

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