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Tractable Reasoning about Agent Programming in Dynamic Preference Logic

Marlo Souza, Alvaro Moreira, Renata Vieira
2018 2018 7th Brazilian Conference on Intelligent Systems (BRACIS)  
In this work, we use of Dynamic Preference Logic to provide a semantic foundation to BDI agent programming languages and investigate tractable expressive fragments of this logic to reason about agent programs  ...  More yet, the reasoning problems in these logics, being based on modal logic, are not tractable in general, limiting their usage to tackle real-world problems.  ...  REASONING ABOUT BDI AGENTS USING DPL An interesting property of Preference Logic -the logic used as a foundation to construct L ≤P ,≤D (A) -is that preference models can be encoded by means of some structures  ... 
doi:10.1109/bracis.2018.00070 dblp:conf/bracis/SouzaMV18 fatcat:ss5xgs5m4vgphplxa3klb32wz4

Special Issue on Challenges for Reasoning under Uncertainty, Inconsistency, Vagueness, and Preferences

Gabriele Kern-Isberner, Thomas Lukasiewicz
2017 Künstliche Intelligenz  
artificial intelligence (AI).  ...  Important examples are fuzzy and probabilistic approaches for description logics, or rule systems for handling vagueness and uncertainty in the Semantic Web, or formalisms for handling user preferences  ...  reasoning, but also libraries for dealing with agents, multi-agent systems.  ... 
doi:10.1007/s13218-016-0479-z fatcat:rdduceqyzzatljzzbmlo2vhjty

Agent-based consumer learning in e-commerce

Xiaoqing Li
2007 International Journal of Networking and Virtual Organisations  
The intelligent agents can play a right role in the personalized education of online consumers, because intelligent agents can learn the consumers' learning preferences and styles and recommend the best  ...  This paper investigates using intelligent agents to support consumer learning and proposes an agent-based consumer learning support framework.  ...  You prefer using your body, hands and sense of touch. • Logical. You prefer using logic, reasoning and systems. • Social. You prefer to learn in groups or with other people. • Solitary.  ... 
doi:10.1504/ijnvo.2007.012083 fatcat:svkklv353nbmtiw577dk2ayfma

AAAI 2002 Workshops

M. Brian Blake, Karen Zita Haigh, Henry Hexmoor, Rino Falcone, Leen-Kiat Soh, Chitta Baral, Sheila A. McIlraith, Piotr J. Gmytrasiewicz, Simon Parsons, Rainer Malaka, Antonio Krüger, Paolo Bouquet (+19 others)
2002 The AI Magazine  
In addition, preferences can themselves be objects of reasoning.  ...  Presentations covered several space systems and a large naval application. Discussions of applied research motivated the need for agents to explicitly reason about autonomy and delegation.  ...  representing and reasoning about either space or time-or both.  ... 
doi:10.1609/aimag.v23i4.1678 dblp:journals/aim/BlakeHHFSBMGPMKBSKPBdJDDRSGWGHIWAGL02 fatcat:b3lkuxmpj5ezbddwbysfuk4yhi

Embedding Ethical Principles in Collective Decision Support Systems

Joshua Greene, Francesca Rossi, John Tasioulas, Kristen Venable, Brian Williams
Thus hybrid collective decision making systems will be in great need.  ...  In this scenario, both machines and collective decision making systems should follow some form of moral values and ethical principles (appropriate to where they will act but always aligned to humans'),  ...  Acknowledgements This work is partially supported by the project "Safety constraints and ethical principles in collective decision making systems" funded by the Future of Life Institute.  ... 
doi:10.1609/aaai.v30i1.9804 fatcat:5dunsyt4e5as5e3sckrva4z4ru

Intelligent System for Real-Time Traffic Recommendations

Pedro Pérez, César Cárdenas, Jorge Ramírez
2014 Research in Computing Science  
This paper proposes a multi-agent system able to make recommendations of travel routes in real time.  ...  This information is given to an agent-based app that, supported on the preferences and needs of the user, presents recommendations of optimal routes.  ...  Implementation using Multi-agent System A multi-agent system is an autonomous computer system, in which there are software agents with a certain level of intelligence.  ... 
doi:10.13053/rcs-76-1-12 fatcat:q56ytva3nvd2jd42zkturfkbmi

Representing and Reasoning with Preferences

Toby Walsh
2007 The AI Magazine  
In multiagent systems, we may need to com- bine the preferences of several agents.  ...  Reasoning about Soft Con- tial Optimization.  ... 
doi:10.1609/aimag.v28i4.2068 dblp:journals/aim/Walsh07 fatcat:i2zhiqv26fhzxj627kt4vn57di

The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents

Nick Bostrom
2012 Minds and Machines  
This paper discusses the relation between intelligence and motivation in artificial agents, developing and briefly arguing for two theses.  ...  In combination, the two theses help us understand the possible range of behavior of superintelligent agents, and they point to some potential dangers in building such an agent.  ...  Others may also have preferences about an agent's goals.  ... 
doi:10.1007/s11023-012-9281-3 fatcat:hsoq3btvxfdrbjfkp467l3l4je

OWL-Based User Preference and Behavior Routine Ontology for Ubiquitous System [chapter]

Kim Anh Pham Ngoc, Young-Koo Lee, Sung-Young Lee
2005 Lecture Notes in Computer Science  
The main benefit of this model is the ability to reason over context data to predict what the user wants the system to do.  ...  In this paper, we propose a formal and comprehensive ontology-based model of user preference and behavior routine.  ...  Introduction Intelligent ubiquitous computing focuses on merging intelligent and agent-based system with the ubiquitous computing paradigm.  ... 
doi:10.1007/11575801_43 fatcat:jiaezcq7rzg43btdzij62amd7i

Page 3502 of Psychological Abstracts Vol. 91, Issue 9 [page]

2004 Psychological Abstracts  
In this paper, we consider multi-agent constraint systems with preferences, modeled as soft constraint systems in which variables and constraints are distributed among multiple autonomous agents.  ...  Preferences recently gained a lot of interest in differ- ent subareas of AI such as qualitative decision theory, nonmonotonic reason- ing, constraint programming (CP), and reasoning about action and time  ... 

Conversational intelligence analysis

Alice Toniolo, Alun D. Preece, Will Webberley, Timothy J. Norman, Paul Sullivan, Timothy Dropps
2016 Proceedings of the 17th International Conference on Distributed Computing and Networking - ICDCN '16  
The integrated system is developed for supporting intelligence analysis in a coalition environment.  ...  CISpaces supports collaborative sensemaking among analysts via argumentation-based evidential reasoning to guide the identification of plausible hypotheses, including reasoning about provenance to explore  ...  The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies, either expressed or implied, of the U.S.  ... 
doi:10.1145/2833312.2849568 dblp:conf/icdcn/TonioloPWNSD16 fatcat:chcnr4gsubfxhg7jzqqp6oyytu

Emergency Management and Decision Support Systems

Mohamed M. El Hadi
2010 مجلة الجمعیة المصریة لنظم المعلومات وتکنولوجیا الحاسبات  
Intelligent DSS and Intelligent Agent Technology (IAT) and their development in an organization are being discussed in this paper.  ...  It identifies a decision making model and its requirement>s definitions of reasoning mechanism and compare both the passive and active DSS.  ...  could have: *A structural intelligence of multi-agent system, or *Behavioral intelligence of multi-functional system.  ... 
doi:10.21608/jstc.2010.120280 fatcat:xrgg537mfjhpfix73xjprsnqvu

Reasoned Assumptions and Pareto Optimality

Jon Doyle
1985 International Joint Conference on Artificial Intelligence  
Default and non-monotonic inference rules are not really epistemological statements, but are instead desires or preferences of the agent about, the makeup of its own mental state (episternic or otherwise  ...  The fundamental relation in non-monotonic logic is not so much self-knowledge as self-choire or seIf-determination, and the fundamental justification of the interpretation"*, and structures involved come  ...  Hanvey and one of the IJCAI referees for discovering an error in an earlier draft.  ... 
dblp:conf/ijcai/Doyle85 fatcat:2ycdvqizwfhqhfvz2pryjdgd3i

Defining an Architecture for a Ubiquitous Group Decision Support System [chapter]

Diogo Martinho, João Carneiro, Goreti Marreiros, Paulo Novais
2017 Advances in Intelligent Systems and Computing  
It uses three main components that are interconnected and that will allow to collect and preserve the amount and quality of intelligence generated in face-to-face meetings.  ...  Supporting group decision-making in ubiquitous contexts is fundamental while developing Group Decision Support Systems (GDSS).  ...  The reasoning layer allows the participant agent to reason about the received information, whether it receives a request or another kind of message.  ... 
doi:10.1007/978-3-319-61118-1_30 fatcat:bxnxicomfjck5kdpdsfftohzea

Crowd Intelligence in Intelligent Environments: A Journey from Complexity to Collectivity

Idham Ananta, Vic Callaghan, Jeannette Chin, Matthew Ball, Michael Gardner
2013 2013 9th International Conference on Intelligent Environments  
One form of complexity in intelligent environments arises from their heterogeneous nature.  ...  However we argue that utilizing Crowd Intelligence techniques in Intelligent Environments offer several advantages for dealing with these complexities.  ...  agent reasoning in favour of the people.  ... 
doi:10.1109/ie.2013.40 dblp:conf/intenv/AnantaCCBG13 fatcat:ihacfv5czvch7jtrpfa72y6rfi
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