Decision theory: an introduction to the mathematics of rationality
Decision theory: an introduction to the mathematics of rationality
Guarantees for autonomy in cognitive agent architecture
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Redesigning the agents' decision machinery
Affective interactions
Autonomy through value-driven goal adoption
International Joint Conference, 7th Ibero-American Conference, 15th Brazilian Symposium on AI, IBERAMIA-SBIA 2000, Open Discussion Track Proceedings on AI
Tax compliance in a simulated heterogeneous multi-agent society
MABS'05 Proceedings of the 6th international conference on Multi-Agent-Based Simulation
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Agents must decide, i.e., choose a preferred option from among a large set of alternatives, according to the precise context where they are immersed. Such a capability defines to what extent they are autonomous. But, there is no one way of deciding, and the classical mode of taking utility functions as the sole support is not adequate for situations constrained by qualitative features (such as wine selection, or putting together a football team). The BVG agent architecture relies on the use of values (multiple dimensions against which to evaluate a situation) to perform choice among a set of candidate goals. In this paper, we propose that values can also be used to guide the adoption of new goals from other agents. We argue that agents should base their rationalities on choice rather than search.