Functional Architecture for Autonomous Vehicle Operations

Beck, Johannes; Knoll, Alexander; Kopp, Sven; Merz, Maximilian

doi:10.2514/6.2009-1969

Cited by 4 publications

(1 citation statement)

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“…Comparing to the biological counter parts, the current agents are still too machine-like. Thus, a cognitive system that gives agents some intelligence and enables them to learn about their dynamic environment and make decisions cognitively is necessary [1][2][3][4][5][6] . In particular, some U.S. research funding agencies have recently identified the needs for developing intelligent agents "… with the capability for situation awareness, allows for greater degree of uncertainty in terms of reasoning systems and produces greater robustness and adaptability in planning algorithms in dealing with unexpected interruptions and rapidly changing objective."…”

Section: Nomenclaturementioning

confidence: 99%

A Biopsychically Inspired Cognitive System for Intelligent Agents in Aerospace Applications

Graham

Basawaraj

et al. 2012

Infotech@Aerospace 2012

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The current state-of-the-art machine intelligence cannot meet the challenges of uncertainty, complexity, time urgency and rapidly changing nature of the dynamic environment in many demanding aerospace applications, such as autonomous extraterrestrial exploration. A biopsychically inspired cognitive system is proposed based on the biological Central Nervous System architecture. The main cognitive units, Decision Making and Planning, Motivation & Learning and Long-term Memory are explained in detail. The algorithms derived from the Central Nervous System and former works on motivated learning are shown for motivation, memory, attention switching, decision making, and planning together with obtained simulation results. The proposed cognitive system can be used for intelligent agents for autonomous scientific exploration, as well as in agriculture, rescue and military applications or as a basis for cooperative groups.

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