Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Babak Esfandiari"'
Publikováno v:
Journal of Sensor and Actuator Networks, Vol 9, Iss 4, p 56 (2020)
Autonomous systems developed with the Belief-Desire-Intention (BDI) architecture tend to be mostly implemented in simulated environments. In this project we sought to build a BDI agent for use in the real world for campus mail delivery in the tunnel
Externí odkaz:
https://doaj.org/article/476726be231347468e5efbcdb5264ca0
Publikováno v:
Communications and Network. 12:99-121
We present an effective routing solution for the backbone of hierarchical MANETs. Our solution leverages the storage and retrieval mechanisms of a Distributed Hash Table (DHT) common to many (structured) P2P overlays. The DHT provides routing informa
Autor:
Jason Miller, Babak Esfandiari
Publikováno v:
Engineering Multi-Agent Systems ISBN: 9783030974565
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6334e527c66e1682eda464118162799
https://doi.org/10.1007/978-3-030-97457-2_13
https://doi.org/10.1007/978-3-030-97457-2_13
Autor:
Patrick Gavigan, Babak Esfandiari
Publikováno v:
Engineering Multi-Agent Systems ISBN: 9783030974565
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bae209df56590332760c197ffd2c2af9
https://doi.org/10.1007/978-3-030-97457-2_8
https://doi.org/10.1007/978-3-030-97457-2_8
Autor:
Babak Esfandiari, Patrick Gavigan
Publikováno v:
Electronics
Volume 10
Issue 17
Electronics, Vol 10, Iss 2136, p 2136 (2021)
Volume 10
Issue 17
Electronics, Vol 10, Iss 2136, p 2136 (2021)
This paper provides the Agent in a Box for developing autonomous mobile robots using Belief-Desire-Intention (BDI) agents. This framework provides the means of connecting the agent reasoning system to the environment, using the Robot Operating System
Autor:
Mohamed Zalat, Babak Esfandiari
Publikováno v:
FLAIRS Conference
We propose five new domain-independent metrics for evaluating and comparing performance at imitating a state-based expert. We use two agents in the RoboCup environment to compare the performance metrics: an agent based on a Multi-Layer Perceptron (ML
Publikováno v:
Journal of Sensor and Actuator Networks, Vol 9, Iss 56, p 56 (2020)
Journal of Sensor and Actuator Networks
Volume 9
Issue 4
AREA@ECAI
Journal of Sensor and Actuator Networks
Volume 9
Issue 4
AREA@ECAI
Autonomous systems developed with the Belief-Desire-Intention (BDI) architecture are usually mostly implemented in simulated environments. In this project we sought to build a BDI agent for use in the real world for campus mail delivery in the tunnel
Autor:
Babak Esfandiari, Michael J. Vezina
Publikováno v:
The Multi-Agent Programming Contest 2019 ISBN: 9783030592981
The Multi-Agent Programming Contest
The Multi-Agent Programming Contest
The 2019 Multi-Agent Programming Contest (MAPC) scenario poses many challenges for agents participating in the contest. We discuss The Requirement Gatherers’ (TRG) approach to handling the various challenges we faced—including how we designed our
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5dd9c2f4c0b922545b371af84de0164
https://doi.org/10.1007/978-3-030-59299-8_5
https://doi.org/10.1007/978-3-030-59299-8_5
Autor:
Cristina Ruiz-Martin, Patrick Gavigan, Alan Davoust, Babak Esfandiari, Gabriel Wainer, Guillermo G. Trabes, Jeremy James
Publikováno v:
Engineering Multi-Agent Systems ISBN: 9783030514167
EMAS@AAMAS
EMAS@AAMAS
We present Simulated Autonomous Vehicle Infrastructure (SAVI), an open source architecture for integrating Belief-Desire-Intention (BDI) agents with a simulation platform. This allows for separation of concerns between the development of complex mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cc2e8434f00c2f6653cd43c0d10bb9f
https://doi.org/10.1007/978-3-030-51417-4_4
https://doi.org/10.1007/978-3-030-51417-4_4
Autor:
Babak Esfandiari, Michael W. Floyd
Publikováno v:
Applied Intelligence. 48:4338-4354
Learning by observation agents learn to perform a behaviour by watching an expert perform that behaviour. The ability of the agents to learn correctly is therefore related to the quality and coverage of the observations. This article presents two nov