Displaying similar documents to “Emotion learning: Solving a shortest path problem in an arbitrary deterministic environment in linear time with an emotional agent”

Epoch-incremental reinforcement learning algorithms

Roman Zajdel (2013)

International Journal of Applied Mathematics and Computer Science

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In this article, a new class of the epoch-incremental reinforcement learning algorithm is proposed. In the incremental mode, the fundamental TD(0) or TD(λ) algorithm is performed and an environment model is created. In the epoch mode, on the basis of the environment model, the distances of past-active states to the terminal state are computed. These distances and the reinforcement terminal state signal are used to improve the agent policy.

The maximum capacity shortest path problem : generation of efficient solution sets

T. Brian Boffey, R. C. Williams, B. Pelegrín, P. Fernandez (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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Individual items of flow in a telecommunications or a transportation network may need to be separated by a minimum distance or time, called a “headway”. If link dependent, such restrictions in general have the effect that the minimum time path for a “convoy” of items to travel from a given origin to a given destination will depend on the size of the convoy. The Quickest Path problem seeks a path to minimise this convoy travel time. A closely related bicriterion problem is the Maximum...

Uncertainty models of vision sensors in mobile robot positioning

Piotr Skrzypczyński (2005)

International Journal of Applied Mathematics and Computer Science

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This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot...

Ant algorithm for flow assignment in connection-oriented networks

Krzysztof Walkowiak (2005)

International Journal of Applied Mathematics and Computer Science

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This work introduces ANB (bf Ant Algorithm for bf Non-bf Bifurcated Flows), a novel approach to capacitated static optimization of flows in connection-oriented computer networks. The problem considered arises naturally from several optimization problems that have recently received significant attention. The proposed ANB is an ant algorithm motivated by recent works on the application of the ant algorithm to solving various problems related to computer networks. However, few works concern...

Combination of mobile agent and evolutionary algorithm to optimize the client transport services

Hayfa Zgaya, Slim Hammadi, Khaled Ghédira (2008)

RAIRO - Operations Research

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This paper presents a migration strategy for a set of mobile agents (MAs) in order to satisfy customers' requests in a transport network, through a multimodal information system. In this context, we propose an optimization solution which operates on two levels. The first one aims to constitute a set of MAs building their routes, called Workplans. At this level, Workplans must incorporate all nodes, representing information providers in the multimodal network, in order to explore it...