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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F12%3A00191556%21RIV13-MSM-21230___
rdf:type
n12:Vysledek skos:Concept
rdfs:seeAlso
http://ksco.info/ksco-2012.html
dcterms:description
The development of control algorithms for tactical missions is being impeded by the significant gap between the way the artificial intelligence (A.I.) algorithms have been designed and validated and the way the robotic applications for (high-fidelity simulations) of tactical missions are being developed. On the one hand, we have low-level robotic simulators (or even robotic field testing). On the other hand, we have synthetic - usually mathematically defined - environments used for the design and formal testing of A.I. algorithms, e.g. randomly generated problem instances, synthetic graph structures, logical structures, regular grids, and similar. In this work, we are proposing a development process and a related software toolkit helping to narrow this gap. We use the simulation-aided development approach and tailor it towards the domain of tactical missions. The process is demonstrated on a specific application scenario, employing a general software toolkit Alite to glue together and adapt a number of A.I. algorithms, originally designed as highly abstract. The development of control algorithms for tactical missions is being impeded by the significant gap between the way the artificial intelligence (A.I.) algorithms have been designed and validated and the way the robotic applications for (high-fidelity simulations) of tactical missions are being developed. On the one hand, we have low-level robotic simulators (or even robotic field testing). On the other hand, we have synthetic - usually mathematically defined - environments used for the design and formal testing of A.I. algorithms, e.g. randomly generated problem instances, synthetic graph structures, logical structures, regular grids, and similar. In this work, we are proposing a development process and a related software toolkit helping to narrow this gap. We use the simulation-aided development approach and tailor it towards the domain of tactical missions. The process is demonstrated on a specific application scenario, employing a general software toolkit Alite to glue together and adapt a number of A.I. algorithms, originally designed as highly abstract.
dcterms:title
Multi-agent Simulation Approach to Development of Applications for Decentralized Tactical Missions Multi-agent Simulation Approach to Development of Applications for Decentralized Tactical Missions
skos:prefLabel
Multi-agent Simulation Approach to Development of Applications for Decentralized Tactical Missions Multi-agent Simulation Approach to Development of Applications for Decentralized Tactical Missions
skos:notation
RIV/68407700:21230/12:00191556!RIV13-MSM-21230___
n12:predkladatel
n17:orjk%3A21230
n4:aktivita
n14:Z
n4:aktivity
Z(MSM6840770038)
n4:dodaniDat
n11:2013
n4:domaciTvurceVysledku
n6:4696530 n6:4450140 n6:2490013
n4:druhVysledku
n19:O
n4:duvernostUdaju
n15:S
n4:entitaPredkladatele
n8:predkladatel
n4:idSjednocenehoVysledku
152299
n4:idVysledku
RIV/68407700:21230/12:00191556
n4:jazykVysledku
n16:eng
n4:klicovaSlova
multi-agent simulation; decentralized environment; software toolkit
n4:klicoveSlovo
n7:decentralized%20environment n7:software%20toolkit n7:multi-agent%20simulation
n4:kontrolniKodProRIV
[E5AE6DF59F6D]
n4:obor
n9:JC
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:rokUplatneniVysledku
n11:2012
n4:tvurceVysledku
Komenda, Antonín Čáp, Michal Pěchouček, Michal
n4:zamer
n10:MSM6840770038
n13:organizacniJednotka
21230