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Intelligent association selection of embedded agents in intelligent inhabited environments

Hakan Duman, Hani Hagras, Vic Callaghan
2007 Pervasive and Mobile Computing  
Furthermore, these artefacts can also be equipped with embedded agents to provide intelligent reasoning, planning and learning capabilities.  ...  Recent advances in technology and manufacturing have resulted in more powerful and smaller processors to be embedded in the various artefacts within smart environments.  ...  embedded agents and IIE issues.  ... 
doi:10.1016/j.pmcj.2006.06.001 fatcat:exoleitjnvhftcqi7sij7ypbwi

Creating an Ambient-Intelligence Environment Using Embedded Agents

H. Hagras, V. Callaghan, M. Colley, G. Clarke, A. Pounds-Cornish, H. Duman
2004 IEEE Intelligent Systems  
In these The Essex intelligent dormitory, iDorm, uses embedded agents to create an ambientintelligence environment.  ...  The embedded agent discreetly controls the iDorm according to user preferences.  ...  Intelligent embedded agents Embedded intelligence refers to including some capacity for reasoning, planning, and learning in an artifact.  ... 
doi:10.1109/mis.2004.61 fatcat:dtmyke766fer3gqbdv3nmx5oeq

The Design of Intelligent Decomposed LMS with Embedded Ganglia Agent

Fu-Chien Kao, Chih-Hong Wang, Ting-Hao Huang, Wen-Yu Chang
2009 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks  
The connection program embedded in the PC of the learner via LMS connects to the Ganglia agent for access to required teaching materials from each LCMS.  ...  This paper proposes an intelligent learning management system with load-balancing function based on Grid structure that allows for the replication of learning materials and balance of network traffic.  ...  Instead, the API Adapter is contained in the LCMS for data transmission and embedded in the LMS web page via dynamic hyperlinks.  ... 
doi:10.1109/i-span.2009.40 dblp:conf/ispan/KaoWHC09 fatcat:bed5lsgfv5hoxeh46v54o4bbuu

An Adaptive Multi Embedded-Agent Architecture for Intelligent Inhabited Environments [chapter]

Elias Tawil, Hani Hagras
2004 Applications and Science in Soft Computing  
Our architecture had learnt successfully the coordination of real world embedded agents operating in changing and dynamic IIE.  ...  In this paper we present an architecture to automate how heterogeneous Intelligent Inhabited Environments (IIE) agents cooperate, in an adaptive and scalable manner.  ...  Embedded-agents are networked physical products that contain intelligent processes that enable them to co-operate to achieve common goals. In IIE, embedded-agents are heterogeneous.  ... 
doi:10.1007/978-3-540-45240-9_37 fatcat:gmwtw5nxirhu7dpzhx6ntj5dxa

A Fuzzy Embedded Agent-Based Approach for Realizing Ambient Intelligence in Intelligent Inhabited Environments

F. Doctor, H. Hagras, V. Callaghan
2005 IEEE transactions on systems, man and cybernetics. Part A. Systems and humans  
In this paper, we describe a novel life-long learning approach for intelligent agents that are embedded in intelligent environments.  ...  He is also interested in embedded agents and intelligent machines. Mr. Doctor is a Student Member of the IEE. Hani Hagras (M'03) received the B.Sc. and M.Sc.  ...  In our previous paper, we developed an incremental synchronous learning technique for an embedded agent [10] ; however, it learned only the user rules and not all the parameters of the embedded agent  ... 
doi:10.1109/tsmca.2004.838488 fatcat:noflbnj5yneapf63s3hjtmjph4

Adjusting Word Embeddings by Deep Neural Networks

Xiaoyang Gao, Ryutaro Ichise
2017 Proceedings of the 9th International Conference on Agents and Artificial Intelligence  
We show that adjustment can be done on word embeddings in both unsupervised and supervised ways.  ...  However the qualities of word embeddings depend on the corpus selected. As for word2vec, we observe that the vectors are far apart to each other.  ...  Polysemous words spread widely in the representation space, far from their similar words, whileICAART 2017 -9th International Conference on Agents and Artificial Intelligence  ... 
doi:10.5220/0006120003980406 dblp:conf/icaart/GaoI17 fatcat:gnlm2fmj3nhipnbmyitvjzano4

Online Learning and Adaptation for Intelligent Embedded Agents Operating in Domestic Environments [chapter]

Hani Hagras, Victor Callaghan, Martin Colley, Graham Clarke, Hakan Duman
2003 Studies in Fuzziness and Soft Computing  
In this paper we show how intelligent embedded agents situated in an intelligent domestic environment can perform learning and adaptation.  ...  In this paper we will introduce the learning and adaptation mechanisms needed by the Building and Robotic embedded agents to fulfil their missions in intelligent domestic environments.  ...  and embedded-agent issues.  ... 
doi:10.1007/978-3-7908-1767-6_11 fatcat:ks5luk3xqzestd6visobqh64rq

Cooperative learning model based on multi-agent architecture for embedded intelligent systems

Monica Villaverde, David Perez, Felix Moreno
2014 IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society  
This paper provides an alternative to improve the reliability of a previous intelligent identification system. The proposed approach implements a cooperative model based on multi-agent architecture.  ...  This new system is composed of several radar-based systems which identify a detected object and transmit its own partial result by implementing several agents and by using a wireless network to transfer  ...  Multiagent architecture An intelligent agent is a virtual entity that needs external information to act accordingly in order to achieve its predetermined purpose.  ... 
doi:10.1109/iecon.2014.7048892 dblp:conf/iecon/VillaverdePM14 fatcat:pc6qj6y54jhcrexhi2mi4gcukq

A Specialised Architecture for Embedding Trust Evaluation Capabilities in Intelligent Mobile Agents [chapter]

Justin R. Pike, Elizabeth M. Ehlers, Ockmer L. Oosthuizen
2009 Lecture Notes in Computer Science  
The evaluator agent is presented as a rational agent with an embedded intelligent trust evaluation capability.  ...  The research also identifies architectural abstractions suitable for developing agents capable of intelligent trust evaluation.  ...  Agents may be 'intelligent' because 'intelligence' is embedded within these agents. That is to say that through software engineering efforts these agents are given the ability to act intelligently.  ... 
doi:10.1007/978-3-642-01639-4_38 fatcat:hcgkt2horjdgjmusts5hetnbf4

Continuous and Embedded Learning for Multi-Agent Systems

Zsolt Kira, Alan Schultz
2006 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems  
This paper describes multi-agent strategies for applying Continuous and Embedded Learning (CEL).  ...  We show that communication of agent status (e.g. failures) among the team members allows the agents to dynamically adapt to team properties, in this case team size.  ...  ACKNOWLEDGMENT Fig. 1 . 1 Left: The Continuous and Embedded Learning Model (from [1]).  ... 
doi:10.1109/iros.2006.282343 dblp:conf/iros/KiraS06 fatcat:gef756fnzbcrdgbg7mnw457i5q

Modelling the Semantic Change Dynamics using Diachronic Word Embedding

Mohamed Boukhaled, Benjamin Fagard, Thierry Poibeau
2019 Proceedings of the 11th International Conference on Agents and Artificial Intelligence  
The model that we propose is based on the long short-term memory units architecture of recurrent neural networks trained on diachronic word embeddings.  ...  which includes early works that aimed at characterizing the evolution through statistical and mathematical modelling (Bailey 1973; Kroch 1989 ) and more recent and advanced works involving artificial intelligence  ...  The predicted embedding ̂ is then compared to the ground truth word embedding in order to assess the prediction accuracy.  ... 
doi:10.5220/0007698109440951 dblp:conf/icaart/BoukhaledFP19 fatcat:b4ogbhkj7jd4rfapzu5crdqnvy

Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence

Namdi Brandon, Kathie L Dionisio, Kristin Isaacs, Rogelio Tornero-Velez, Dustin Kapraun, R Woodrow Setzer, Paul S Price
2018 Journal of Exposure Science and Environmental Epidemiology  
By basing the ABM upon an artificial intelligence (AI) system, we create agents that mimic human decisions on performing behaviors relevant for determining exposures to chemicals and other stressors.  ...  Herein we create an agent-based model (ABM) that simulates longitudinal patterns in human behavior.  ...  models embedded with needs-based artificial. . .  ... 
doi:10.1038/s41370-018-0052-y pmid:30242268 pmcid:PMC6914672 fatcat:meilni5ikrddjgp5jrxgnanz2y

An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments

Hani Hagras, Faiyaz Doctor, Victor Callaghan, Antonio Lopez
2007 IEEE transactions on fuzzy systems  
In this paper, we present a novel adaptive embedded agent architecture for Ambient Intelligent Environments (AIEs) that is based on interval type-2 fuzzy systems.  ...  The presented type-2 agent architecture is suited for the embedded platforms used in AIEs which have limited computational and memory capabilities.  ...  Embedded agents [4] , [15] are embedded computational artefacts integrated with intelligent reasoning and learning mechanisms.  ... 
doi:10.1109/tfuzz.2006.889758 fatcat:zpe2fgobvfbnziwrf6bcx4rqt4

About Some Specificities of Embedded Multiagent Systems Design

Jean-Paul Jamont, Michel Occello
2007 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07)  
Even if we are at the beginning of the expansion of embedded MAS, we are sure that embedded MAS methods will be the continuation of traditional embedded system design lifecycle.  ...  Although this phase is informal, it allows designers to clearly separate the various aspects embedded within the application. We must choose here the architecture of the different agents.  ... 
doi:10.1109/iat.2007.71 dblp:conf/iat/JamontO07 fatcat:ylfbjwffpveq3pbd6sr6q7s37u

Large Margin Nearest Neighbor Embedding for Knowledge Representation

Miao Fan, Qiang Zhou, Thomas Fang Zheng, Ralph Grishman
2015 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)  
Inspired by the success in applying Distributed Representations to AI-related fields, recent studies expect to represent each entity and relation with a unique lowdimensional embedding, which is different  ...  We thus contribute an effective model to learn better embeddings satisfying the formula by pulling the positive tail entities t + together and close to h + r (Nearest Neighbor), and simultaneously pushing  ...  The intuitive goal of our model is to learn embeddings of positive tail entities t + closer to h + r than any other negative embeddings t − .  ... 
doi:10.1109/wi-iat.2015.125 dblp:conf/webi/FanZZG15 fatcat:24r4wj6ayjf4rat2mki75zisbu
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