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Titlebook: Agents and Artificial Intelligence; Third International Joaquim Filipe,Ana Fred Conference proceedings 2013 Springer-Verlag Berlin Heidelb

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https://doi.org/10.1057/9781137013941r on the function. With these features it is possible to classify fitness functions and to identify a parameter set which leads to an equal or better optimization process compared to the standard parameter set for Particle Swarm Optimization.
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Cultural Work and Higher Educationuce the complexity of computing the optimal strategy in problems where only some of the dimensions of the problem are controllable. The approach is applied to aircraft collision avoidance where the system must recommend maneuvers to an imperfect pilot.
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Ethnicity (Not Race) and Belonging,s, the reasoning on the emotional state of agents is only performed for the very next future, generating behavior that is myopic for middle or long term goals. In this paper, we propose instead a deliberative model based on automated planning that integrates all these features for long term reasoning.
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Setting Up Particle Swarm Optimization by Decision Tree Learning Out of Function Featuresr on the function. With these features it is possible to classify fitness functions and to identify a parameter set which leads to an equal or better optimization process compared to the standard parameter set for Particle Swarm Optimization.
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Collision Avoidance Using Partially Controlled Markov Decision Processesuce the complexity of computing the optimal strategy in problems where only some of the dimensions of the problem are controllable. The approach is applied to aircraft collision avoidance where the system must recommend maneuvers to an imperfect pilot.
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Cultural Work and Higher Education SRM is acceptable in the sense that cross-validation, if performed, would probably indicate the same complexity. We consider a non-stratified variant of cross-validation, which is convenient for the main theorem.
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Early Contacts Between Bali and India desires and intentions, and decide to cope or not with the norms while dropping, retaining or adopting new intentions. The applicability of our approach is demonstrated through an non-combatant evacuation scenario implemented by using the Normative Jason platform.
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