Abstract
Often, decision making involves autonomous agents that are structured in a complex hierarchy, representing e.g. authority. Typically the agents share the same body of knowledge, but each may have its own, possibly conflicting, preferences on the available information.
We model the common knowledge base for such preference agents as a logic program under the extended answer set semantics, thus allowing for the defeat of rules to resolve conflicts. An agent can express its preferences on certain aspects of this information using a partial order relation on either literals or rules. Placing such agents in a hierarchy according to their position in the decision making process results in a system where agents cooperate to find solutions that are jointly preferred.
We show that a hierarchy of agents with either preferences on rules or on literals can be transformed into an equivalent system with just one type of preferences. Regarding the expressiveness, the formalism essentially covers the polynomial hierarchy. E.g. the membership problem for a hierarchy of depth n is \(\sum{_{n+2}^P}\) -complete. We illustrate an application of the approach by showing how it can easily express a generalization of weak constraints, i.e. “desirable” constraints that do not need to be satisfied but where one tries to minimize their violation.
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Heymans, S., Van Nieuwenborgh, D., Vermeir, D. (2004). Hierarchical Decision Making by Autonomous Agents. In: Alferes, J.J., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2004. Lecture Notes in Computer Science(), vol 3229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30227-8_7
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DOI: https://doi.org/10.1007/978-3-540-30227-8_7
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