The blackboard model of problem solving
AI Magazine
Computer algebra (2nd ed.): systems and algorithms for algebraic computation
Computer algebra (2nd ed.): systems and algorithms for algebraic computation
Case-based reasoning
Symbolic integration I: transcendental functions
Symbolic integration I: transcendental functions
Symbolic integration: the stormy decade
Communications of the ACM
Strategic negotiation in multiagent environments
Strategic negotiation in multiagent environments
Critical Agents Supporting Interactive Theorem Proving
EPIA '99 Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
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Coordination of multiple autonomous agents to solve problems that require each of them to contribute their limited expertise in the construction of a solution is often ensured by the use of numerical methods such as vote-counting, payoff functions, game theory and economic criteria. In areas where there are no obvious numerical methods for agents to use in assessing other agents' contributions, many questions still remain open for research. The paper reports a study of one such area: heuristic indefinite integration in terms of agents with different single heuristic abilities which must cooperate in finding indefinite integrals. It examines the reasons for successes and lack of success in performance, and draws some general conclusions about the usefulness of indefinite integration as a field for realistic tests of methods for multi-agent systems where the usefulness of "economic" criteria is limited. In this connection, the role of numerical taxonomy is emphasised.