A bottom-up mechanism for behavior selection in an artificial creature
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Modeling motivations and emotions as a basis for intelligent behavior
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Knowledge Growth in an Artificial Animal
Proceedings of the 1st International Conference on Genetic Algorithms
Relating behavior selection architectures to environmental complexity
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Modeling adaptive autonomous agents
Artificial Life
Cognitive agents based simulation for decisions regarding human team composition
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
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Embodied autonomous agents are systems that inhabit dynamic, unpredictable environments in which they try to satisfy a set of time-dependent goals or motivations in order to survive. One of the problems that this implies is action selection, the task of resolving conflicts between competing behavioral alternatives. We present an experimental comparison of two action selection mechanisms (ASM), implementing "winner-takes-all" (WTA) and "voting-based" (VB) policies respectively, modeled using a motivational behavior-based approach. This research shows the adequacy of these two ASM with respect to different sources of environmental complexity and the tendency of each of them to show different behavioral phenomena.