Naoki Ohta

Coalition structure generation utilizing compact characteristic function representations

This paper presents a new way of formalizing the Coalition Structure Generation problem (CSG), so that we can apply constraint optimization techniques to it. Forming effective coalitions is a major research challenge in AI and multi-agent systems. CSG involves partitioning a set of agents into coalitions so that social surplus is maximized. Traditionally, the input of the CSG problem is a black-box function called a characteristic function, which takes a coalition as an input and returns the value of the coalition. As a result, applying constraint optimization techniques to this problem has been infeasible. However, characteristic functions that appear in practice often can be represented concisely by a set of rules, rather than a single black-box function. Then, we can solve the CSG problem more efficiently by applying constraint optimization techniques to the compact representation directly. We present new formalizations of the CSG problem by utilizing recently developed compact representation schemes for characteristic functions.We first characterize the complexity of the CSG under these representation schemes. In this context, the complexity is driven more by the number of rules rather than by the number of agents. Furthermore, as an initial step towards developing efficient constraint optimization algorithms for solving the CSG problem, we develop mixed integer programming formulations and show that an off-the-shelf optimization package can perform reasonably well, i.e., it can solve instances with a few hundred agents, while the state-of-the-art algorithm (which does not make use of compact representations) can solve instances with up to 27 agents.

MapReduce-Based Implementation of a Rule System

As information and communication technologies advance, large amounts of data are created everyday. The demands for processing such big data are also increasing. To meet them, the MapReduce framework has been proposed and is now widely used. On the other hand, a rule-based system is used to implement such an intelligent system as an expert system. For applying a rule-based system to process large amounts of data, we propose a method that implements a rule system based on the MapReduce framework. We constructed a simple rule system using Hadoop, which is an open source implementation of the MapReduce framework, and compared several methods of executing a rule system. Our experimental results indicate the potential of a rule system implemented using the MapReduce framework.

Coalition structure generation in cooperative games with compact representations

This paper presents a new way of formalizing the coalition structure generation problem (CSG) so that we can apply constraint optimization techniques to it. Forming effective coalitions is a major research challenge in AI and multi-agent systems. CSG involves partitioning a set of agents into coalitions to maximize social surplus. Traditionally, the input of the CSG problem is a black-box function called a characteristic function, which takes a coalition as input and returns the value of the coalition. As a result, applying constraint optimization techniques to this problem has been infeasible. However, characteristic functions that appear in practice often can be represented concisely by a set of rules, rather than treating the function as a black box. Then we can solve the CSG problem more efficiently by directly applying constraint optimization techniques to this compact representation. We present new formalizations of the CSG problem by utilizing recently developed compact representation schemes for characteristic functions. We first characterize the complexity of CSG under these representation schemes. In this context, the complexity is driven more by the number of rules than by the number of agents. As an initial step toward developing efficient constraint optimization algorithms for solving the CSG problem, we also develop mixed integer programming formulations and show that an off-the-shelf optimization package can perform reasonably well.

Toward a Supporting System of Communication Skill: The Influence of Functional Roles of Participants in Group Discussion

More and more companies are putting emphasis on communication skill in the recruitment of their employees and are adopting group discussion as part of recruitment interview. In our project, we aim to develop a system that can provide advices to its users in improving the impression of their communication skill during group discussion. In this paper, we focus on the functional roles of the participants in group discussion and report the results of the analysis of the relationship between communication skill impression and functional roles. This work is based on a group discussion corpus of 40 participants. The participants’ communication skill of the corpus was evaluated by 21 external experts who had experience of recruitment. In addition, seven functional roles: Follower, Gatekeeper, Information giver, Objector, Opinion provider, Passive participant, and Summarizer were defined and annotated. Furthermore, we analyzed the conversational situations of corpus and the difference of between participants with high-score and low-score communication skill in these situations.

An Integer Programming Approach for Two-Sided Matching with Indifferences

To make use of the collective intelligence of many autonomous self-interested agents, it is important to form a team on which all the agents agree. Two-sided matching is one of the basic approaches to form a team that consists of agents from two disjoint agent groups. Traditional two-sided matching assumes that an agent has a totally ordered preference list of the agents it is to be paired with, but it is unrealistic to have a totally ordered list for a large-scale two-sided matching problem. In this paper, we propose an integer programming based approach to solve a two-sided matching program that allows indifferences in agents’ preferences, and show how an objective function can be defined to find a matching that minimizes the maximum discontentedness of agents in one group.

Composing the Atmosphere of a Virtual Classroom with a Group of Student Agents

In Japan, the training of teachers mainly relies on in-classroom lectures in universities. It is compensated with the practice for a relatively short period, say only two to three weeks in real schools. The teacher-training programs in Japan therefore lacks the practice of teaching skills and the admission of classes. The result is, many young teachers left their jobs in the first year due to frustration and other mental issues. In order to relieve this situation, we are developing a Wizard-of-OZ (WOZ) based simulation platform of a school environment with computer graphics (CG) animated virtual students. The trainees can interact with the virtual students in this immersive and realistic virtual classroom and practice their teaching and administration skills. The virtual students are operated by an operator (the wizard) from remote with a dedicated interface. In addition to the training purpose, the system is considered to be able to be used in the examination of teacher recruitment as well. In that case, the operator is supposed to be the examination investigator.

Integer Programming Based Stable and Efficiency Algorithm for Two-sided Matching with Indifferences

To make use of collective intelligence of many autonomous self-interested agents, it is important to form a team that all the agents agree. Two-sided matching is one of the basic approaches to form a team that consists of agents from two disjoint agent groups. Traditional two-sided matching assumes that an agent has totally ordered preference list of agents to be paired with. However, it is unrealistic to have a totally ordered list for a large-scale two-sided matching problem. Therefore, two-sided matching with indifferences is proposed. It allows indifferences in the preference list of agents. Two-sided matching with indifferences has two important characters weakly stable and Pareto efficiency. In this paper, we propose a new integer programming based algorithm “nucleolus” for two-sided matching with indifferences. This algorithm propose the matching which satisfies weakly stable and Pareto efficiency.

Changeable two-sided matching for changing environment

Two-sided matching is a major matching problem for players in two groups. If a player joins or leaves a group, the matching must be calculated from scratch. In this paper, we propose a changeable two-sided matching problem for two-sided problems in changing environments where a player can join or leave groups. We also propose an algorithm, called the continuation algorithm, for this problem, which calculates matching using not only the preferences of the players of the two groups, but also the matching result of the original two-sided matching problem before changes occur. We demonstrate that, if the matching result of the original two-sided matching is stable, the result obtained by the continuation algorithm is also stable.

A new solution concept for coalitional games in open anonymous environments

Coalition formation is a key aspect of automated negotiation among self-interested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Various solution concepts (such as the Shapley value, core, least core, and nucleolus) have been proposed. In this paper, we demonstrate how these concepts are vulnerable to various kinds of manipulations in open anonymous environments such as the Internet. These manipulations include submitting false names (one acting as many), collusion (many acting as one), and the hiding of skills. To address these threats, we introduce a new solution concept called the anonymity-proof core, which is robust to these manipulations. We show that the anonymity-proof core is characterized by certain simple axiomatic conditions. Furthermore, we show that by relaxing these conditions, we obtain a concept called the least anonymity-proof core, which is guaranteed to be non-empty.