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Takayuki Ito

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25 papers
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25

AAMAS Conference 2022 Conference Paper

Augmented Democratic Deliberation: Can Conversational Agents Boost Deliberation in Social Media?

  • Rafik Hadfi
  • Takayuki Ito

Online social media are currently perceived as the new means of providing a platform for participation among citizens. This comes at a time when people are led to alternative spaces of political expression as traditional channels become strained. New technologies appear to have a transformational potential that could lead to social change and achieve deeper and wider mobilisation in political processes. However, people still face challenges when seeking information, disseminating information, or engaging in online deliberation. Allowing every citizen to participate in discussions and thus influence the final decision requires countless interactions that take considerable amounts of time and energy. This process is cognitively demanding due to linguistic barriers or when the problems on the table are multidisciplinary. We envision in this blue sky paper the development of autonomous and intelligent conversational agents that can augment the deliberative capacities of citizens in social media. To implement our vision, we start by proposing an approach that quantifies deliberation in online argumentative discussions. Then, we propose a methodology to optimise deliberation across discussion threads. The proposed concept is expected to pave the way to a form of augmented democratic deliberation built on the cooperation of humans and conversational agents.

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AAAI Conference 2020 System Paper

D-Agree: Crowd Discussion Support System Based on Automated Facilitation Agent

  • Takayuki Ito
  • Shota Suzuki
  • Naoko Yamaguchi
  • Tomohiro Nishida
  • Kentaro Hiraishi
  • Kai Yoshino

Large-scale online discussion platforms are receiving great attention as potential next-generation methods for smart democratic citizen platforms. One of the studies clarified the critical problem faced by human facilitators caused by the difficulty of facilitating large-scale online discussions. In this demonstration, we present our current implementation of D-agree, a crowd-scale discussion support system based on an automated facilitation agent. We conducted a large-scale social experiment with Nagoya local government. The results demonstrate that the agent worked well compared with human facilitators.

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AAAI Conference 2020 Short Paper

Optimal Auction Based Automated Negotiation in Realistic Decentralised Market Environments

  • Pankaj Mishra
  • Ahmed Maustafa
  • Takayuki Ito
  • Minjie Zhang

Automated negotiations based on learning models have been widely applied in different domains of negotiation. Specifically, for resource allocation in decentralised open market environments with multiple vendors and multiple buyers. In such open market environments, there exists dynamically changing supply and demand of resources, with dynamic arrival of buyers in the market. Besides, each buyer has their own set of constraints, such as budget constraints, time constraints, etc. In this context, efficient negotiation policies should be capable of maintaining the equilibrium between the utilities of both the vendors and the buyers. In this research, we aim to design a mechanism for an optimal auction paradigm, considering the existence of interdependent undisclosed preferences of both, buyers and vendors. Therefore, learning-based negotiation models are immensely appropriate for such open market environments; wherein, self-interested autonomous vendors and buyers cooperate/compete to maximize their utilities based on their undisclosed preferences. Toward this end, we present our current proposal, the two-stage learning-based resource allocation mechanism, wherein utilities of vendors and buyers are optimised at each stage. We are aiming to compare our proposed learning-based resource allocation mechanism with two state-of-the-art bidding-based resource allocation mechanism, which are based on, fixed bidding policy (Samimi, Teimouri, and Mukhtar 2016) and demand-based bidding policy (Kong, Zhang, and Ye 2015). The comparison is to be done based on the overall performance of the open market environment and also based on the individual performances of vendors and buyers.

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AAAI Conference 2017 Conference Paper

Automated Negotiating Agents Competition (ANAC)

  • Catholijn Jonker
  • Reyhan Aydogan
  • Tim Baarslag
  • Katsuhide Fujita
  • Takayuki Ito
  • Koen Hindriks

The annual International Automated Negotiating Agents Competition (ANAC) is used by the automated negotiation research community to benchmark and evaluate its work andto challenge itself. The benchmark problems and evaluation results and the protocols and strategies developed are available to the wider research community.

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AAMAS Conference 2016 Conference Paper

Multilayered Multiagent System for Traffic Simulation (Demonstration)

  • Rafik Hadfi
  • Takayuki Ito

We propose a multilayered multiagent simulator that can simulate traffic in any urban environment on earth, subject to specific weather conditions. We adopt an agent-based approach for the behaviors of the vehicles and the drivers. We additionally propose a behavioral model to realistically emulate the driving behaviors of humans.

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IJCAI Conference 2013 Conference Paper

Efficient Interdependent Value Combinatorial Auctions with Single Minded Bidders

  • Valentin Robu
  • David C. Parkes
  • Takayuki Ito
  • Nicholas R. Jennings

We study the problem of designing efficient auctions where bidders have interdependent values; i. e. , values that depend on the signals of other agents. We consider a contingent bid model in which agents can explicitly condition the value of their bids on the bids submitted by others. In particular, we adopt a linear contingent bidding model for single minded combinatorial auctions (CAs), in which submitted bids are linear combinations of bids received from others. We extend the existing state of the art, by identifying constraints on the interesting bundles and contingency weights reported by the agents which allow the efficient second priced, fixed point bids auction to be implemented in single minded CAs. Moreover, for domains in which the required single crossing condition fails (which characterizes when efficient, IC auctions are possible), we design a two-stage mechanism in which a subset of agents (“experts”) are allocated first, using their reports to allocate the remaining items to the other agents.

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AIJ Journal 2013 Journal Article

Evaluating practical negotiating agents: Results and analysis of the 2011 international competition

  • Tim Baarslag
  • Katsuhide Fujita
  • Enrico H. Gerding
  • Koen Hindriks
  • Takayuki Ito
  • Nicholas R. Jennings
  • Catholijn Jonker
  • Sarit Kraus

This paper presents an in-depth analysis and the key insights gained from the Second International Automated Negotiating Agents Competition (ANAC 2011). ANAC is an international competition that challenges researchers to develop successful automated negotiation agents for scenarios where there is no information about the strategies and preferences of the opponents. The key objectives of this competition are to advance the state-of-the-art in the area of practical bilateral multi-issue negotiations, and to encourage the design of agents that are able to operate effectively across a variety of scenarios. Eighteen teams from seven different institutes competed. This paper describes these agents, the setup of the tournament, including the negotiation scenarios used, and the results of both the qualifying and final rounds of the tournament. We then go on to analyse the different strategies and techniques employed by the participants using two methods: (i) we classify the agents with respect to their concession behaviour against a set of standard benchmark strategies and (ii) we employ empirical game theory (EGT) to investigate the robustness of the strategies. Our analysis of the competition results allows us to highlight several interesting insights for the broader automated negotiation community. In particular, we show that the most adaptive negotiation strategies, while robust across different opponents, are not necessarily the ones that win the competition. Furthermore, our EGT analysis highlights the importance of considering metrics, in addition to utility maximisation (such as the size of the basin of attraction), in determining what makes a successful and robust negotiation agent for practical settings.

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JAAMAS Journal 2010 Journal Article

Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces

  • Miguel A. Lopez-Carmona
  • Ivan Marsa-Maestre
  • Takayuki Ito

Abstract Negotiating contracts with multiple interdependent issues may yield non- monotonic, highly uncorrelated preference spaces for the participating agents. These scenarios are specially challenging because the complexity of the agents’ utility functions makes traditional negotiation mechanisms not applicable. There is a number of recent research lines addressing complex negotiations in uncorrelated utility spaces. However, most of them focus on overcoming the problems imposed by the complexity of the scenario, without analyzing the potential consequences of the strategic behavior of the negotiating agents in the models they propose. Analyzing the dynamics of the negotiation process when agents with different strategies interact is necessary to apply these models to real, competitive environments. Specially problematic are high price of anarchy situations, which imply that individual rationality drives the agents towards strategies which yield low individual and social welfares. In scenarios involving highly uncorrelated utility spaces, “low social welfare” usually means that the negotiations fail, and therefore high price of anarchy situations should be avoided in the negotiation mechanisms. In our previous work, we proposed an auction-based negotiation model designed for negotiations about complex contracts when highly uncorrelated, constraint-based utility spaces are involved. This paper performs a strategy analysis of this model, revealing that the approach raises stability concerns, leading to situations with a high (or even infinite) price of anarchy. In addition, a set of techniques to solve this problem are proposed, and an experimental evaluation is performed to validate the adequacy of the proposed approaches to improve the strategic stability of the negotiation process. Finally, incentive-compatibility of the model is studied.

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IJCAI Conference 2009 Conference Paper

  • Ivan Marsa-Maestre
  • Miguel A. Lopez-Carmona
  • Juan R. Velasco
  • Takayuki Ito
  • Mark Klein
  • Katsuhide Fujita

Negotiation scenarios involving nonlinear utility functions are specially challenging, because traditional negotiation mechanisms cannot be applied. Even mechanisms designed and proven useful for nonlinear utility spaces may fail if the utility space is highly nonlinear. For example, although both contract sampling and constraint sampling have been successfully used in auction based negotiations with constraint-based utility spaces, they tend to fail in highly nonlinear utility scenarios. In this paper, we will show that the performance of these approaches decrease drastically in highly nonlinear utility scenarios, and propose a mechanism which balances utility and deal probability for the bidding and deal identification processes. The experiments show that the proposed mechanisms yield better results than the previous approaches in highly nonlinear negotiation scenarios.

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AAMAS Conference 2008 Conference Paper

A Preliminary result on a representative-based multi-round protocol for multi-issue negotiations

  • Katsuhide Fujita
  • Takayuki Ito
  • Mark Klein

Multi-issue negotiation protocols represent a promising field since most negotiation problems in the real world involve multiple issues. Our work focuses on negotiation with interdependent issues, in which agent utility functions are nonlinear. Existing works have not yet focused on agents’ private information. In addition, they were not scalable in the sense that they have shown a high failure rate for making agreements among 5 or more agents. In this paper, we focus on a novel multi-round representative-based protocol that utilizes the amount of agents’ private information revealed. Experimental results demonstrate that our mechanism reduces the failure rate in making agreements, and it is scalable on the number of agents compared with existing approaches.

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IJCAI Conference 2007 Conference Paper

  • Takayuki Ito
  • Hiromitsu HATTORI
  • Mark Klein

Multi-issue negotiation protocols have been studied widely and represent a promising field since most negotiation problems in the real world involve multiple issues. The vast majority of this work has assumed that negotiation issues are independent, so agents can aggregate the utilities of the issue values by simple summation, producing linear utility functions. In the real world, however, such aggregations are often unrealistic. We cannot, for example, just add up the value of car's carburetor and the value of car's engine when engineers negotiate over the design a car. These value of these choices are interdependent, resulting in nonlinear utility functions. In this paper, we address this important gap in current negotiation techniques. We propose a negotiation protocol where agents employ adjusted sampling to generate proposals, and a bidding-based mechanism is used to find social-welfare maximizing deals. Our experimental results show that our method substantially outperforms existing methods in large nonlinear utility spaces like those found in real world contexts.

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AAMAS Conference 2007 Conference Paper

Online Auctions for Bidders with Interdependent Values

  • Florin Constantin
  • Takayuki Ito
  • David C. Parkes

Interdependent values (IDV) is a valuation model allowing bidders in an auction to express their value for the item(s) to sell as a function of the other bidders' information. We investigate the incentive compatibility (IC) of single-item auctions for IDV bidders in dynamic environments. We provide a necessary and sufficient characterization for IC in this setting. We show that if bidders can misreport departure times and private signals, no reasonable auction can be IC. We present a reasonable IC auction for the case where bidders cannot misreport departures.

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AAMAS Conference 2007 Conference Paper

Scaling-Up Shopbots - a Dynamic Allocation-Based Approach

  • David Sarne
  • Sarit Kraus
  • Takayuki Ito

In this paper we consider the problem of eCommerce comparison shopping agents (shopbots) that are limited by capacity constraints. In light of the phenomenal increase both in demand for price comparison services over the internet and in the number of opportunities available in electronic markets, shopbots are nowadays required to improve the utilization of their finite set of querying resources. In this paper we introduce PlanBot, an innovative shopbot which uniquely integrates concepts from production management and economic search theory. PlanBot aims to maximize its efficiency by dynamically re-planning the allocation of its querying resources according to the results of formerly executed queries and new arriving requests. We detail the design principles that drive the PlanBot 's operation and illustrate its improved performance (in comparison to the traditional shopbots' First-Come-First-Served (FCFS) query execution mechanisms) using a simulated environment which is based on price datasets collected over the internet. Our encouraging results suggest that the design principles we apply have the potential of being used as an infrastructure for various implementations of future comparison shopping agents.

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AAMAS Conference 2007 Conference Paper

Using Iterative Narrowing to Enable Multi-Party Negotiations with Multiple Interdependent Issues

  • Hiromitsu HATTORI
  • Mark Klein
  • Takayuki Ito

Multi-issue negotiations are a central part of many coordination challenges, and thus represent an important research topic. Almost all previous work in this area has assumed that negotiation issues are independent, but this is rarely the case in real-world contexts. Our work focuses on negotiation with interdependent issues and, therefore, nonlinear (multi-optimum) agent utility functions. Since the utility functions are typically very complex, the challenge becomes finding high-quality negotiation outcomes without making unrealistic demands concerning how much agents reveal about their utilities. Since negotiations often involve more than two parties, the approach should also be scalable. In this paper, we propose a novel protocol for addressing these challenges, wherein agents approach agreements by iteratively narrowing the space of possible agreements. In the early stages, agents submit rough bids representing promising regions from their utility functions. In later stages, they submit increasingly narrow bids for the subset of those regions that the negotiating parties all liked. We show that our method outperforms existing methods in large nonlinear utility spaces, and is computationally feasible for negotiations with as many as ten agents.

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AAAI Conference 2006 Conference Paper

A Negotiation Protocol for Agents with Nonlinear Utility Functions

  • Takayuki Ito

Multi-issue negotiation protocols have been studied widely and represent a promising field since most negotiation problems in the real world involve multiple issues. The vast majority of this work has assumed that negotiation issues are independent, so agents can aggregate the utilities of the issue values by simple summation, producing linear utility functions. In the real world, however, such aggregations are often unrealistic. We cannot, for example, just add up the value of car's carburetor and the value of car's engine when engineers negotiate over the design a car. These value of these choices are interdependent, resulting in nonlinear utility functions. In this paper, we address this important gap in current negotiation techniques. We propose a negotiation protocol where agents employ adjusted sampling to generate proposals, and an auction mechanism is used to find social-welfare maximizing deals. Our experimental results show that our method substantially outperforms existing methods in large nonlinear utility spaces like those found in real world contexts. Further, we show that our protocol is incentive compatible.

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AAAI Conference 2005 Conference Paper

A New Strategy-Proof Greedy-Allocation Combinatorial Auction Protocol and Its Extension to Open Ascending Auction Protocol

  • Takayuki Ito
  • Shigeo Matsubara

This paper proposes a new combinatorial auction protocol called Average-Max-Minimal-Bundle (AM-MB) protocol. The characteristics of the AM-MB protocol are as follows: (i) it is strategyproof, i. e. , truth-telling is a dominant strategy, (ii) the computational overhead is very low, since it allocates bundles greedily thereby avoiding an explicit combinatorial optimization problem, and (iii) it can obtain higher social surplus and revenue than can the Max-Minimal-Bundle (M-MB) protocol, which also satisÞes (i) and (ii). Furthermore, this paper extends the AM-MB protocol to an open ascending-price protocol in which straightforward bidding is an ex-post Nash equilibrium.

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