Author name cluster
Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.
AIJ Journal 2013 Journal Article
IJCAI Conference 2013 Conference Paper
Persuasion is a common social and economic activity. It usually arises when conflicting interests among agents exist, and one of the agents wishes to sway the opinions of others. This paper considers the problem of an automated agent that needs to influence the decision of a group of self-interested agents that must reach an agreement on a joint action. For example, consider an automated agent that aims to reduce the energy consumption of a nonresidential building, by convincing a group of people who share an office to agree on an economy mode of the air-conditioning and low light intensity. In this paper we present four problems that address issues of minimality and safety of the persuasion process. We discuss the relationships to similar problems from social choice, and show that if the agents are using Plurality or Veto as their voting rule all of our problems are in P. We also show that with K-Approval, Bucklin and Borda voting rules some problems become intractable. We thus present heuristics for efficient persuasion with Borda, and evaluate them through simulations.
AAMAS Conference 2012 Conference Paper
As agents’ technology becomes increasing more prevalent, coordination in mixed agent-human environments becomes a key issue. Agent-human coordination is becoming even more important in real life situations, where uncertainty and incomplete information exists and communication is costly. While abundant research has focused on aspects of computerized teamwork, little attention has been given to the issues raised in teams that consist of both computerized agents and people. In this paper we focus on teamwork between an agent and a human counterpart and present a novel agent designed to interact proficiently with people. In extensive simulations we matched our agent with people and compared it with another state-of-the-art agent. Our results demonstrate the significant improvement in coordination when our agent is involved.
AAAI Conference 2012 Conference Paper
Coordination in mixed agent-human environments is an important, yet not a simple, problem. Little attention has been given to the issues raised in teams that consist of both computerized agents and people. In such situations different considerations are in order, as people tend to make mistakes and they are affected by cognitive, social and cultural factors. In this paper we present a novel agent designed to proficiently coordinate with a human counterpart. The agent uses a neural network model that is based on a pre-existing knowledge base which allows it to achieve an efficient modeling of a human’s decisions and predict their behavior. A novel communication mechanism which takes into account the expected effect of communication on the other member will allow communication costs to be minimized. In extensive simulations involving more than 200 people we investigated our approach and showed that our agent achieves better coordination when involved, compared to settings in which only humans or another state-of-the-art agent are involved.
IS Journal 2011 Journal Article
The automated, animated mediator AniMed* aims to increase the social welfare of people in bilateral negotiations, utilizing a generic strategy mechanism and the ability to propose partial solutions.
AAAI Conference 2011 Conference Paper
The interaction of people with autonomous agents has become increasingly prevalent. Some of these settings include security domains, where people can be characterized as uncooperative, hostile, manipulative, and tending to take advantage of the situation for their own needs. This makes it challenging to design proficient agents to interact with people in such environments. Evaluating the success of the agents automatically before evaluating them with people or deploying them could alleviate this challenge and result in better designed agents. In this paper we show how Peer Designed Agents (PDAs) – computer agents developed by human subjects – can be used as a method for evaluating autonomous agents in security domains. Such evaluation can reduce the effort and costs involved in evaluating autonomous agents interacting with people to validate their efficacy. Our experiments included more than 70 human subjects and 40 PDAs developed by students. The study provides empirical support that PDAs can be used to compare the proficiency of autonomous agents when matched with people in security domains.
AAMAS Conference 2011 Conference Paper
Autonomy requires robustness. The use of unmanned (autonomous) vehicles is appealing for tasks which are dangerous or dull. However, increased reliance on autonomous robots increases reliance on their robustness. Even with validated software, physical faults can cause the controlling software to perceive the environment incorrectly, and thus to make decisions that lead to task failure. We present an online anomaly detection method for robots, that is light-weight, and is able to take into account a large number of monitored sensors and internal measurements, with high precision. We demonstrate a specialization of the familiar Mahalanobis Distance for robot use, and also show how it can be used even with very large dimensions, by online selection of correlated measurements for its use. We empirically evaluate these contributions in different domains: commercial Unmanned Aerial Vehicles (UAVs), a vacuum-cleaning robot, and a high-fidelity flight simulator. We find that the online Mahalanobis distance technique, presented here, is superior to previous methods.
ICRA Conference 2010 Conference Paper
The use of unmanned autonomous vehicles is becoming more and more significant in recent years. The fact that the vehicles are unmanned (whether autonomous or not), can lead to greater difficulties in identifying failure and anomalous states, since the operator cannot rely on its own body perceptions to identify failures. Moreover, as the autonomy of unmanned vehicles increases, it becomes more difficult for operators to monitor them closely, and this further exacerbates the difficulty of identifying anomalous states, in a timely manner. Model-based diagnosis and fault-detection systems have been proposed to recognize failures. However, these rely on the capabilities of the underlying model, which necessarily abstracts away from the physical reality of the robot. In this paper we propose a novel, model-free, approach for detecting anomalies in unmanned autonomous vehicles, based on their sensor readings (internal and external). Experiments conducted on Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) demonstrate the efficacy of the approach by detecting the vehicles deviations from nominal behavior.
AAAI Conference 2010 Conference Paper
Computer agents are increasingly deployed in settings in which they make decisions with people, such as electronic commerce, collaborative interfaces, and cognitive assistants. However, the scientific evaluation of computational strategies for human-computer decision-making is a costly process, involving time, effort and personnel. This paper investigates the use of Peer Designed Agents (PDA)—computer agents developed by human subjects—as a tool for facilitating the evaluation process of automatic negotiators that were developed by researchers. It compares the performance between automatic negotiators that interacted with PDAs to automatic negotiators that interacted with actual people in different domains. The experiments included more than 300 human subjects and 50 PDAs developed by students. Results showed that the automatic negotiators outperformed PDAs in the same situations in which they outperformed people, and that on average, they exhibited the same measure of generosity towards their negotiation partners. These patterns occurred for all types of domains, and for all types of automated negotiators, despite the fact that there were individual differences between the behavior of PDAs and people. The study thus provides an empirical proof that PDAs can alleviate the evaluation process of automatic negotiators, and facilitate their design.
AAMAS Conference 2009 Conference Paper
Automated negotiation agents capable of negotiating efficiently with people must deal with the fact that people are diverse in their behavior and each individual might negotiate in a different manner. Thus, automated agents must rely on a good opponent modeling component to model their counterpart and adapt their behavior to their partner. In this paper we present the KBAgent. The KBAgent is an automated negotiator that negotiates with each person only once, and uses past negotiation sessions of others as a knowledge base for general opponent modeling. The database is used to extract the likelihood of acceptance and proposals that may be offered by the opposite side. Experiments conducted with people show that the KBAgent negotiates efficiently with people and even achieves better utility values than another automated negotiator, shown to be efficient in negotiations with people. Moreover, the KBAgent achieves significantly better agreements, in terms of individual utility, than the human counterparts playing the same role.
AAMAS Conference 2009 Conference Paper
Negotiation surrounds our day-to-day lives. Research in the field of automated negotiations has suggested the design and use of automated negotiators, on one hand to allow facilitation of the negotiation process by human negotiators and, on the other hand to provide automated agents that can negotiate on behalf of humans. Many papers present innovative agents and evaluate their efficacy in negotiations with other automated agents or people. Others focus on building negotiation support systems with the purpose of helping negotiators reach an agreement. Yet, the question still remains whether these systems or agents have the potential of improving people’s negotiation skills. In this paper we attempt to shed more light on this topic. By means of extensive simulations with human negotiators we examine and compare several training methods and their implications on the improvement of negotiation skills of human negotiators.
AIJ Journal 2008 Journal Article
AAMAS Conference 2008 Conference Paper
As computerized agents are becoming more and more common, e-commerce becomes a major candidate for incorporation of automated agents. Thus, it is vital to understand how people design agents for online markets and how their design changes over time. This, in turn, will enable better design of agents for these environments. We focus on the design of trading agents for bilateral negotiations with unenforceable agreements. In order to simulate this environment we conducted an experiment with human subjects who were asked to design agents for a resource allocation game. The subjects’ agents participated in several tournaments against each other and were given the opportunity to improve their agents based on their performance in previous tournaments. Our results show that, indeed, most subjects modified their agents’ strategic behavior with the prospect of improving the performance of their agents, yet their average score significantly decreased throughout the tournaments and became closer to the equilibrium agents’ score. In particular, the subjects modified their agents to break more agreements throughout the tournaments. In addition, the subjects increased their means of protection against deceiving agents.
AAMAS Conference 2007 Conference Paper
As more and more cars are equipped with GPS and Wi-Fi transmitters, it becomes easier to design systems that will allow cars to interact autonomously with each other, e. g. , regarding traffic on the roads. Indeed, car manufacturers are already equipping their cars with such devices. Though, currently these systems are a proprietary, we envision a nat- ural evolution where agent applications will be developed for vehicular systems, e. g. , to improve car routing in dense urban areas. Nonetheless, this new technology and agent ap- plications may lead to the emergence of self-interested car owners, who will care more about their own welfare than the social welfare of their peers. These car owners will try to manipulate their agents such that they transmit false data to their peers. Using a simulation environment, which mod- els a real transportation network in a large city, we demon- strate the benefits achieved by self-interested agents if no counter-measures are implemented.
ECAI Conference 2006 Conference Paper
Many day-to-day tasks require negotiation, mostly under conditions of incomplete information. In particular, the opponent's exact tradeoff between different offers is usually unknown. We propose a model of an automated negotiation agent capable of negotiating with a bounded rational agent (and in particular, against humans) under conditions of incomplete information. Although we test our agent in one specific domain, the agent's architecture is generic; thus it can be adapted to any domain as long as the negotiators' preferences can be expressed in additive utilities. Our results indicate that the agent played significantly better, including reaching a higher proportion of agreements, than human counterparts when playing one of the sides, while when playing the other side there was no significant difference between the results of the agent and the human players.