Foundations of distributed interaction systems

  • Authors:

  • Marat Fayzullin;Mirco Nanni;Dino Pedreschi;V. S. Subrahmanian

  • Affiliations:

  • Computer Science Department, University of Maryland, College Park, MD 20742, USA Email: {fms,vs}@cs.umd.edu;Dipartimento di Informatica, Universita di Pisa, Corso Italia 40, 56125 Pisa, Italy Email: {nnanni,pedre}@di.unipi.it;Dipartimento di Informatica, Universita di Pisa, Corso Italia 40, 56125 Pisa, Italy Email: {nnanni,pedre}@di.unipi.it;Computer Science Department, University of Maryland, College Park, MD 20742, USA Email: {fms,vs}@cs.umd.edu

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2000

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Abstract

There are numerous applications where a variety of human and software participants interactively pursue a given task (play a game, engage in a simulation, etc.). In this paper, we define a basic architecture for a distributed, interactive system (DIS for short). We then formally define a mathematical construct called a DIS abstraction that provides a theoretical basis for a software platform for building distributed interactive systems. Our framework provides a language for building multiagent applications where each agent has its own behaviors and where the behavior of the multiagent application as a whole is governed by one or more “master” agents. Agents in such a multiagent application may compete for resources, may attempt to take actions based on incorrect beliefs, may attempt to take actions that conflict with actions being concurrently attempted by other agents, and so on. Master agents mediate such conflicts. Our language for building agents (ordinary and master) depends critically on a notion called a “generalized constraint” that we define. All agents attempt to optimize an objective function while satisfying such generalized constraints that the agent is bound to preserve. We develop several algorithms to determine how an agent satisfies its generalized constraints in response to events in the multiagent application. We experimentally evaluate these algorithms in an attempt to understand their advantages and disadvantages.