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2010 22nd IEEE International Conference on Tools with Artificial Intelligence

Date 27-29 Oct. 2010

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  • [Front cover - Vol 2]

    Publication Year: 2010, Page(s): C1
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  • [Title page i - Volume 2]

    Publication Year: 2010, Page(s): i
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  • [Title page iii - Volume 2]

    Publication Year: 2010, Page(s): iii
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  • [Copyright notice - Volume 2]

    Publication Year: 2010, Page(s): iv
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  • Table of contents - Volume 2

    Publication Year: 2010, Page(s):v - ix
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  • Message from the Program Chair - Volume 2

    Publication Year: 2010, Page(s): x
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  • Conference Committees - Volume 2

    Publication Year: 2010, Page(s):xi - xiii
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  • Additional Reviewers - Volume 2

    Publication Year: 2010, Page(s):xiv - xv
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  • Best Paper Award - Volume 2

    Publication Year: 2010, Page(s): xvi
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  • Strategy and Fairness in Repeated Two-agent Interaction

    Publication Year: 2010, Page(s):3 - 6
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (320 KB) | HTML iconHTML

    The criterion of fairness has not been given much attention in the research of multi-agent learning problem. We propose an adaptive strategy for agents to achieve fairness in repeated two-agent game with conflicting interests. In our strategy, each agent is equipped with inequity-averse based fairness model, and makes its decision according to its attractiveness for each action. Besides, each agen... View full abstract»

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  • Creating Possible Worlds Using Sims Tables for the Imperfect Information Card Game Schnapsen

    Publication Year: 2010, Page(s):7 - 10
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (175 KB) | HTML iconHTML

    We discuss a new algorithm for traversing possible worlds in games of imperfect information based on the enumerablity of permutations by means of Sims tables. The resulting anytime capabilities of the algorithm are demonstrated by applying it to the card game Schnapsen, popular in Central Europe. View full abstract»

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  • An Adaptive Prediction-Regret Driven Strategy for Bilateral Bargaining

    Publication Year: 2010, Page(s):11 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (137 KB) | HTML iconHTML

    This paper presents an adaptive prediction-regret driven negotiation strategy for bilateral bargaining without modeling opponents, which combines the prediction idea in heuristic method and the regret principle in psychology. Experimental results show that agents that employ this strategy outperform agents that use other strategies previously proposed in the literature. View full abstract»

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  • Using an Emotional Intelligent Agent to Support Customers' Searches Interactively in e-Marketplaces

    Publication Year: 2010, Page(s):15 - 22
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1412 KB) | HTML iconHTML

    Emotions play a key role in any purchasing process even more when it is done through web portals. In this paper, we present a fuzzy-logic based system aimed to generate emotions for a virtual seller or avatar. The 3D avatar is integrated within the e-Zoco e-commerce portal and its behaviour depends on the product search results. Moreover, the mood of the avatar not only depend on the products that... View full abstract»

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  • Partial Move A*

    Publication Year: 2010, Page(s):25 - 31
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (179 KB) | HTML iconHTML

    Some shortest path problems that can be solved using the A* algorithm have a large branching factor due to the combination of multiple choices at each move. Multiple sequence alignment and multi-agent pathfinding are examples of such problems. If the search can be stopped after each choice instead of being stopped at each combination of choices, it takes much less memory and much less time. The go... View full abstract»

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  • Using Cellular Automata Pedestrian Flow Statistics with Heuristic Search to Automatically Design Spatial Layout

    Publication Year: 2010, Page(s):32 - 37
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (529 KB) | HTML iconHTML

    The spatial layout of public space has an enormous impact upon the ease with which people can move. For example, a well designed public building such as a train station or hospital should allow for the smooth flow of a large number of people. In extreme cases, design can be so poor that during emergency evacuations people have been crushed to death. It is vital that design takes into account the s... View full abstract»

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  • A Nettree for Approximate Maximal Pattern Matching with Gaps and One-Off Constraint

    Publication Year: 2010, Page(s):38 - 41
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (187 KB) | HTML iconHTML

    Recently, pattern matching with flexible gap constraints has attracted extensive attention especially in biological sequence analysis and mining patterns from sequences. An issue is to search Maximal Pattern Matching with Gaps and the One-Off Condition (MPMGOOC). Firstly, we introduce the concept of MPMGOOC. In order to solve the problem, we propose some special concepts of Nettree which is differ... View full abstract»

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  • Software Effort Prediction Using Regression Rule Extraction from Neural Networks

    Publication Year: 2010, Page(s):45 - 52
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (541 KB) | HTML iconHTML

    Neural networks are often selected as tool for software effort prediction because of their capability to approximate any continuous function with arbitrary accuracy. A major drawback of neural networks is the complex mapping between inputs and output, which is not easily understood by a user. This paper describes a rule extraction technique that derives a set of comprehensible IF-THEN rules from a... View full abstract»

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  • Neural Network Rule Extraction and the LED Display Recognition Problem

    Publication Year: 2010, Page(s):53 - 56
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (184 KB) | HTML iconHTML

    This paper presents the results from a neural network rule extraction algorithm applied to the LED display recognition problem. We show that pruned neural networks with small number of hidden nodes and connections are able to recognize all the 10 digits from 0 to 9. Earlier work by other researchers demonstrated how symbolic fuzzy rules can be extracted from trained neural networks to solve this p... View full abstract»

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  • H.264/AVC Intra-only Coding (iAVC) and Neural Network Based Prediction Mode Decision

    Publication Year: 2010, Page(s):57 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (593 KB) | HTML iconHTML

    The requirement to transmit video data over unreliable wireless networks is anticipated in the foreseeable future. Significant compression ratio and error resilience are both needed for applications including tele-operated robotics, vehicle-mounted cameras, sensor network, etc. Block-matching based inter-frame coding techniques, such as MPEG-x and H.26x, do not perform well in these scenarios due ... View full abstract»

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  • Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning

    Publication Year: 2010, Page(s):63 - 70
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (260 KB) | HTML iconHTML

    We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised Learning method for the offline construction of a predictor which takes the problem's parameters as input and infers values for the discrete optimization variables. This way, the online resolution time ... View full abstract»

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  • Integrating Time and Resources into Planning

    Publication Year: 2010, Page(s):71 - 78
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (383 KB) | HTML iconHTML

    AI Planning typically deals with the causal relations between the actions while the role of explicit time and limited resources is suppressed. The recent trends show that integrating time and resource reasoning into planning significantly improves direct applicability of planning technology in real-life problems. In this paper we propose a suboptimal domain-independent planning system Filuta that ... View full abstract»

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  • Combining Learning Techniques for Classical Planning: Macro-operators and Entanglements

    Publication Year: 2010, Page(s):79 - 86
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (223 KB) | HTML iconHTML

    Planning techniques recorded a significant progress during recent years. However, many planning problems remain still hard even for modern planners. One of the most promising approaches is gathering additional knowledge by using learning techniques. Well known sort of knowledge - macro-operators, formalized like 'normal' planning operators, represent a sequence of primitive planning operators. The... View full abstract»

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  • Merging of Temporal Plans Supported by Plan Repairing

    Publication Year: 2010, Page(s):87 - 94
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (367 KB) | HTML iconHTML

    In this paper, we present an approach to coordinate two temporal plans, where one plan is for the achievement of a reactive goal, and thus has more priority, while the other is for the achievement of a proactive goal. As both plans have been computed independently from each other, conflicts can arise during their execution. We present a plan merging algorithm to coordinate the actions of both plan... View full abstract»

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  • TyCo: Towards Typicality-based Collaborative Filtering Recommendation

    Publication Year: 2010, Page(s):97 - 104
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (273 KB) | HTML iconHTML

    Collaborative filtering (CF) is an important and popular technology for recommendation systems. However, current collaborative filtering methods suffer from some problems such as sparsity problem, inaccurate recommendation and producing big-error predictions. In this paper, we borrow ideas of object typicality from cognitive psychology and propose a novel typicality-based collaborative filtering r... View full abstract»

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  • Robust Collaborative Recommendation by Least Trimmed Squares Matrix Factorization

    Publication Year: 2010, Page(s):105 - 112
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (299 KB) | HTML iconHTML

    Collaborative filtering (CF) recommender systems help people discover what they really need in a large set of alternatives by analyzing the preferences of other related users. Recent research has shown that the accuracy of recommendations can be improved significantly by using matrix factorization (MF) models. In particular, a mixed MF model was used by BellKor's Pragmatic Chaos to win the Netflix... View full abstract»

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