Distributed Learning Agents with Motivation for Cellular Warehouse Problem | Zendy

Katsumi HAMA | Zendy; Sadayoshi Mikami | Zendy; Keiji Suzuki | Zendy; Yukinori Kakazu | Zendy

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Distributed Learning Agents with Motivation for Cellular Warehouse Problem

Author(s) -

Katsumi HAMA,

Sadayoshi Mikami,

Keiji Suzuki,

Yukinori Kakazu

Publication year - 2002

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2002.p0088

Subject(s) - pallet , computer science , motion (physics) , distributed computing , multi agent system , autonomous agent , artificial intelligence , operations research , human–computer interaction , engineering , mechanical engineering

In an approach to resolve motion conflicts of transport pallets for cellular warehouse problems, pallets are considered autonomous agents and built-in behavior provided by ANN and problem-oriented connection weights evolved using Evolutionary Programming navigate agents to goals. To determine agents to be moved, priority is introduced and the measure of each agent changes based on the results of its motion and interaction with other agents. The solution of the problem is the motion sequence of agents. The effectiveness of the approach is demonstrated by computer simulation.

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