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Constraint-Based Agents
Autonomous agents have become a vibrant research and development topic in recent years attracting activity and attention from various areas. The basic agent concept incorporates proactive autonomous units with goal-directed-behaviour and communication capabilities. The book focuses on autonomous agents that can act in a goal directed manner under real time constraints and incomplete knowledge, being situated in a dynamic environment where resources may be restricted. To satisfy such complex requirements, the author improves, combines, and applies results from areas like planning, constraint programming, and local search. The formal framework developed is evaluated by application to the field of computer games, which fit the problem context very well since most of them are played in real time and provide a highly interactive environment where environmental situations are changing rapidly.
Integration of AI and OR Techniques in Constraint Programming
This book constitutes the proceedings of the International Conference on the Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, CPAIOR 2014, held in Cork, Ireland, in May 2014. The 33 papers presented in this volume were carefully reviewed and selected from 70 submissions. The papers focus on constraint programming and global constraints; scheduling modelling; encodings and SAT logistics; MIP; CSP and complexity; parallelism and search; and data mining and machine learning.
Data Mining and Constraint Programming
A successful integration of constraint programming and data mining has the potential to lead to a new ICT paradigm with far reaching implications. It could change the face of data mining and machine learning, as well as constraint programming technology. It would not only allow one to use data mining techniques in constraint programming to identify and update constraints and optimization criteria, but also to employ constraints and criteria in data mining and machine learning in order to discover models compatible with prior knowledge. This book reports on some key results obtained on this integrated and cross- disciplinary approach within the European FP7 FET Open project no. 284715 on “Inductive Constraint Programming” and a number of associated workshops and Dagstuhl seminars. The book is structured in five parts: background; learning to model; learning to solve; constraint programming for data mining; and showcases.
KI 2001: Advances in Artificial Intelligence
This volume contains the contributions to the Joint German/Austrian Con- rence on Arti?cial Intelligence, KI 2001, which comprises the 24th German and the 9th Austrian Conference on Arti?cial Intelligence. They are divided into the following categories: – 2 contributions by invited speakers of the conference; – 29 accepted technical papers, of which 5 where submitted as application papers and 24 as papers on foundations of AI; – 4 contributions by participants of the industrial day, during which companies working in the ?eld presented their AI applications. After a long period of separate meetings, the German and Austrian Societies ̈ for Arti?cial Intelligence, KI and OGAI, decided to...
An Introduction to Constraint-Based Temporal Reasoning
Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. This book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. The book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. This book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems.
Advances in Artificial Intelligence - IBERAMIA 2002
The 8th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2002, took place in Spain for the second time in 14 years; the first conference was organized in Barcelona in January 1988. The city of Seville hosted this 8th conference, giving the participants the opportunity of enjoying the richness of its historical and cultural atmosphere. Looking back over these 14 years, key aspects of the conference, such as its structure, organization, the quantity and quality of submissions, the publication policy, and the number of attendants, have significantly changed. Some data taken from IBERAMIA’88 and IBERAMIA 2002 may help to illustrate these changes. IBERAMIA’88 was planned as an i...
AIxIA 2020 – Advances in Artificial Intelligence
This book constitutes the refereed post proceedings of the XIXth International Conference of the Italian Association for Artificial Intelligence, AIxIA 2020, held in Milano, Italy, in November 2020.Due to the COVID-19 pandemic, the conference was "rebooted"/ re-organized w.r.t. the original format. The 27 full papers were carefully reviewed and selected from 89 submissions. The society aims at increasing the public awareness of Artificial Intelligence, encouraging the teaching and promoting research in the field.
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
The 5th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2008) was held in Paris, France May 20–23, 2008. The purpose of this conference series is to bring together researchers in the ?elds of constraint programming, arti?cial intelligence, and operations research to explore ways of solving large-scale, practical optimization problems through integration and hybridization of the ?elds’ di?erent techniques. Through the years, this research community is discovering that the ?elds have much in c- mon, and there has been tremendous richness in the resulting cross-fertilization of ?elds. This year, we all...
Dynamic Flexible Constraint Satisfaction and its Application to AI Planning
First, I would like to thank my principal supervisor Dr Qiang Shen for all his help, advice and friendship throughout. Many thanks also to my second supervisor Dr Peter Jarvis for his enthusiasm, help and friendship. I would also like to thank the other members of the Approximate and Qualitative Reasoning group at Edinburgh who have also helped and inspired me. This project has been funded by an EPSRC studentship, award num ber 97305803. I would like, therefore, to extend my gratitude to EPSRC for supporting this work. Many thanks to the staff at Edinburgh University for all their help and support and for promptly fixing any technical problems that I have had . My whole family have been both...
