5th Hellenic Conference on Artificial Intelligence 2008 SETN’08

Άρθρα Μελών ΕΕΤΝ

Επιλεγμένα άρθρα των μελών της ΕΕΤΝ θα παρουσιαστούν σε ειδική συνεδρία του ΣΕΤΝ’08

A. Xanthopoulos, D.E. Koulouriotis and A. Gasteratos, "A Reinforcement Learning Approach for Production Control in Manufacturing Systems", Proceedings of Int. Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems, European Conference in Artificial Intelligence (ECAI) 2008, Patras, Greece, 2008.

The problem of production control in serial manufacturing lines that consist of a number of unreliable machines linked with intermediate buffers is addressed. We make use of Reinforcement Learning methodologies in order to derive efficient control policies. Our aim is to derive control policies that are more state-dependent and therefore more efficient than well-known pull type control policies such as Kanban. Manufacturing systems of this type are studied under average measures such as average WorkInProcess inventories etc. and thus, a learning algorithm from the currently developing field of Average Reward Reinforcement Learning was applied. The Reinforcement Learning control policy was compared to three existing efficient pull type control policies, namely Kanban, Base Stock and CONWIP on the basis of simulated data and found to outperform them. The simulation experiments involved a single-product system with two machines that allows backordering. Numerical results are presented along with a qualitative interpretation of our findings. The paper concludes with directions for future research.

More info: full paper

I. Refanidis, “Managing Personal Tasks with Time Constraints and Preferences”, Proceedings of the International Conference on Automated Planning and Scheduling, ICAPS 2007, Providence, Rhode Island, USA, 2007.

This paper treats the problem of managing personal tasks, through an adaptation of the Squeaky Wheel Optimization (SWO) framework, enhanced with powerful heuristics and full constraint propagation. The problem involves preemptive and non-preemptive tasks, with extra constraints imposed on the sizes of and the distances between the parts of each preemptive task. Travelling times are imposed by the alternative localization possibilities of each task. Ordering constraints are imposed by the producer-consumer relations between tasks. The user may have preferences regarding scheduling options of single tasks or pairs of tasks. Higher degree time constraints and preferences are supported as well. SWO allows for fast scheduling and rescheduling. Several heuristics are proposed to estimate the difficulty to schedule each task and to compensate with the degree of the user’s satisfaction. Experimental results show that this approach is remarkably effective and efficient.

More info: author’s publications

E. Kontopoulos, N. Bassiliades, G. Antoniou, "Visual Stratification of Defeasible Logic Rule Bases", Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI07), Patras, Greece, 2007.

Logic and proofs constitute key factors in increasing the user trust towards the Semantic Web. Defeasible reasoning is a useful tool towards the development of the Logic layer of the Semantic Web architecture. However, having a solid mathematical notation, it may be confusing to end users, who often need graphical trace and explanation mechanisms for the derived conclusions. In a previous work of ours, we outlined a methodology for representing defeasible logic rules, utilizing directed graphs that feature distinct node and connection types. However, visualizing a defeasible logic rule base also involves the placement of the multiple graph elements in an intuitive way, a non-trivial task that aims at improving user comprehensibility. This paper presents a stratification algorithm for visualizing defeasible logic rule bases that query and reason about RDF data as well as a tool that applies this algorithm.

More info: full paper

C.Theocharopoulou, I. Partsakoulakis, G. Vouros, K. Stergiou, “Overlay Networks for Task Allocation and Coordination in Dynamic Large-scale Networks of Cooperative Agents”, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2007, Honolulu, Hawaii, 2007.

This work proposes a method for allocating temporally interdependent tasks to homogeneous or heterogeneous cooperative agents in dynamic large-scale networks. This method views searching, task allocation and scheduling as an integrated problem that has to be efficiently solved in such networks. Solving the general problem optimally in a decentralized way is very hard and can only be solved by a centralized method, be approximated by means of heuristics, or by relaxations of the original problem. Our method facilitates effective searching through the dynamic assignment of gateway roles to agents and the exploitation of routing indices. In combination to searching, it exploits distributed constraint satisfaction techniques and dynamic re-organization of agent teams to efficiently handle the allocation of complex tasks with interdependent subtasks.

More info: G. Vouros’s publications


    Φωτογραφίες του συνεδρίου

    12/5/2008: Προθεσμία υποβολής άρθρου στην Ειδική Συνεδρία: 31 Μαΐου.

    2/5/2008: Η προθεσμία υποβολής εργασιών παρατείνεται ως τις 19 Μαΐου.

    15/3/2008: Η ηλεκτρονική υποβολή εργασιών είναι ανοιχτή.

    12/3/2008: Ανακοίνωση βραβείου καλύτερου φοιτητικού άρθρου. Λεπτομέρειες θα βρείτε στη σελίδα "Υποβολή Εργασιών".

    10/2/2008: Ανακοίνωση ειδικής συνεδρίας: Applications of AI Research in Engineering Design