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48
Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain
, 2011
"... The concept of creating autonomous agents capable of exhibiting ad hoc teamwork was recently introduced as a challenge to the AI, and specifically to the multiagent systems community. An agent capable of ad hoc teamwork is one that can effectively cooperate with multiple potential teammates on a set ..."
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Cited by 27 (10 self)
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The concept of creating autonomous agents capable of exhibiting ad hoc teamwork was recently introduced as a challenge to the AI, and specifically to the multiagent systems community. An agent capable of ad hoc teamwork is one that can effectively cooperate with multiple potential teammates on a set of collaborative tasks. Previous research has investigated theoretically optimal ad hoc teamwork strategies in restrictive settings. This paper presents the first empirical study of ad hoc teamwork in a more open, complex teamwork domain. Specifically, we evaluate a range of effective algorithms for on-line behavior generation on the part of a single ad hoc team agent that must collaborate with a range of possible teammates in the pursuit domain.
Online Planning for Ad Hoc Autonomous Agent Teams
- PROCEEDINGS OF THE TWENTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
"... We propose a novel online planning algorithm for ad hoc team settings—challenging situations in which an agent must collaborate with unknown teammates without prior coordination. Our approach is based on constructing and solving a series of stage games, and then using biased adaptive play to choose ..."
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Cited by 19 (2 self)
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We propose a novel online planning algorithm for ad hoc team settings—challenging situations in which an agent must collaborate with unknown teammates without prior coordination. Our approach is based on constructing and solving a series of stage games, and then using biased adaptive play to choose actions. The utility function in each stage game is estimated via Monte-Carlo tree search using the UCT algorithm. We establish analytically the convergence of the algorithm and show that it performs well in a variety of ad hoc team domains.
Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates
, 2012
"... The growing use of autonomous agents in practice may require agents to cooperate as a team in situations where they have limited prior knowledge about one another, cannot communicate directly, or do not share the same world models. These situations raise the need to design ad hoc team members, i.e., ..."
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Cited by 18 (4 self)
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The growing use of autonomous agents in practice may require agents to cooperate as a team in situations where they have limited prior knowledge about one another, cannot communicate directly, or do not share the same world models. These situations raise the need to design ad hoc team members, i.e., agents that will be able to cooperate without coordination in order to reach an optimal team behavior. This paper considers the problem of leading N-agent teams by an agent toward their optimal joint utility, where the agents compute their next actions based only on their most recent observations of their teammates’ actions. We show that compared to previous results in two-agent teams, in larger teams the agent might not be able to lead the team to the action with maximal joint utility, thus its optimal strategy is to lead the team to the best possible reachable cycle of joint actions. We describe a graphical model of the problem and a polynomial time algorithm for solving it. We then consider other variations of the problem, including leading teams of agents where they base their actions on longer history of past observations, leading a team by more than one ad hoc agent, and leading a teammate while the ad hoc agent is uncertain of its behavior.
Ad Hoc Teamwork for Leading a Flock
"... Designing agents that can cooperate with other agents as a team, without prior coordination or explicit communication, is becoming more desirable as autonomous agents become more prevalent. In this paper we examine an aspect of the problem of leading teammates in an ad hoc teamwork setting, where th ..."
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Cited by 9 (5 self)
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Designing agents that can cooperate with other agents as a team, without prior coordination or explicit communication, is becoming more desirable as autonomous agents become more prevalent. In this paper we examine an aspect of the problem of leading teammates in an ad hoc teamwork setting, where the designed ad hoc agents lead the other teammates to a desired behavior that maximizes team utility. Specifically, we consider the problem of leading a flock of agents to a desired orientation using a subset of ad hoc agents. We examine the problem theoretically, and set bounds on the extent of influence the ad hoc agents can have on the team when the agents are stationary. We use these results to examine the complicated problem of orienting a stationary team to a desired orientation using a set of nonstationary ad hoc agents. We then provide an empirical evaluation of the suggested solution using our custom-designed simulator FlockSim.
The RoboCup 2013 Drop-In Player Challenges: A Testbed for Ad Hoc Teamwork
, 2014
"... Ad hoc teamwork has recently been introduced as a general challenge for AI and especially multiagent systems [15]. The goal is to en-able autonomous agents to band together with previously unknown teammates towards a common goal: collaboration without pre-coordination. While research to this point ..."
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Cited by 9 (6 self)
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Ad hoc teamwork has recently been introduced as a general challenge for AI and especially multiagent systems [15]. The goal is to en-able autonomous agents to band together with previously unknown teammates towards a common goal: collaboration without pre-coordination. While research to this point has focused mainly on theoretical treatments and empirical studies in relatively simple domains, the long-term vision has always been to enable robots or other autonomous agents to exhibit the sort of flexibility and adaptability on complex tasks that people do, for example when they play games of “pick-up” basketball or soccer. This paper chronicles the first evaluation of autonomous robots doing just that: playing pick-up soccer. Specifically, in June 2013, the authors helped organize a “drop-in player challenge” in three different leagues at the international RoboCup competition. In all cases, the agents were put on teams with no pre-coordination. This paper documents the structure of the challenge, describes some of the strategies used by participants, and analyzes the results.
Teamwork with Limited Knowledge of Teammates
"... While great strides have been made in multiagent teamwork, existing approaches typically assume extensive information exists about teammates and how to coordinate actions. This paper addresses how robust teamwork can still be created even if limited or no information exists about a specific group of ..."
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Cited by 7 (4 self)
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While great strides have been made in multiagent teamwork, existing approaches typically assume extensive information exists about teammates and how to coordinate actions. This paper addresses how robust teamwork can still be created even if limited or no information exists about a specific group of teammates, as in the ad hoc teamwork scenario. The main contribution of this paper is the first empirical evaluation of an agent cooperating with teammates not created by the authors, where the agent is not provided expert knowledge of its teammates. For this purpose, we develop a generalpurpose teammate modeling method and test the resulting ad hoc team agent’s ability to collaborate with more than 40 unknown teams of agents to accomplish a benchmark task. These agents were designed by people other than the authors without these designers planning for the ad hoc teamwork setting. A secondary contribution of the paper is a new transfer learning algorithm, TwoStageTransfer, that can improve results when the ad hoc team agent does have some limited observations of its current teammates. 1
Role-based Ad Hoc Teamwork
, 2011
"... An ad hoc team setting is one in which teammates must work together to obtain a common goal, but without any prior agreement regarding how to work together. In this paper we present a role-based approach for ad hoc teamwork, in which each teammate is inferred to be following a specialized role that ..."
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Cited by 7 (1 self)
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An ad hoc team setting is one in which teammates must work together to obtain a common goal, but without any prior agreement regarding how to work together. In this paper we present a role-based approach for ad hoc teamwork, in which each teammate is inferred to be following a specialized role that accomplishes a specific task or exhibits a particular behavior. In such cases, the role an ad hoc agent should select depends both on its own capabilities and on the roles currently selected by the other team members. We formally define methods for evaluating the influence of the ad hoc agent’s role selection on the team’s utility, leading to an efficient calculation of the role that yields maximal team utility. In simple teamwork settings, we demonstrate that the optimal role assignment can be easily determined. However, in complex environments, where it is not trivial to determine the optimal role assignment, we examine empirically the best suited method for role assignment. Finally, we show that the methods we describe have a predictive nature. As such, once an appropriate assignment method is determined for a domain, it can be used successfully in new tasks that the team has not encountered before and for which only limited prior experience is available.
An analysis framework for ad hoc teamwork tasks
- ADV. MATH
, 2012
"... In multiagent team settings, the agents are often given a protocol for coordinating their actions. When such a protocol is not available, agents must engage in ad hoc teamwork to effectively cooperate with one another. A fully general ad hoc team agent needs to be capable of collaborating with a wid ..."
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Cited by 6 (4 self)
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In multiagent team settings, the agents are often given a protocol for coordinating their actions. When such a protocol is not available, agents must engage in ad hoc teamwork to effectively cooperate with one another. A fully general ad hoc team agent needs to be capable of collaborating with a wide range of potential teammates onavaryingsetofjointtasks. This paper presents a framework for analyzing ad hoc teamproblems that sheds light on the current state of research and suggests avenues for future research. In addition, this paper shows how previous theoretical results can aid ad hoc agents in a set of testbed domains.
Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems.
- In Proc. of AAMAS,
, 2012
"... ABSTRACT This paper is concerned with evaluating different multiagent learning (MAL) algorithms in problems where individual agents may be heterogenous, in the sense of utilizing different learning strategies, without the opportunity for prior agreements or information regarding coordination. Such ..."
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Cited by 5 (3 self)
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ABSTRACT This paper is concerned with evaluating different multiagent learning (MAL) algorithms in problems where individual agents may be heterogenous, in the sense of utilizing different learning strategies, without the opportunity for prior agreements or information regarding coordination. Such a situation arises in ad hoc team problems, a model of many practical multiagent systems applications. Prior work in multiagent learning has often been focussed on homogeneous groups of agents, meaning that all agents were identical and a priori aware of this fact. Also, those algorithms that are specifically designed for ad hoc team problems are typically evaluated in teams of agents with fixed behaviours, as opposed to agents which are adapting their behaviours. In this work, we empirically evaluate five MAL algorithms, representing major approaches to multiagent learning but originally developed with the homogeneous setting in mind, to understand their behaviour in a set of ad hoc team problems. All teams consist of agents which are continuously adapting their behaviours. The algorithms are evaluated with respect to a comprehensive characterisation of repeated matrix games, using performance criteria that include considerations such as attainment of equilibrium, social welfare and fairness. Our main conclusion is that there is no clear winner. However, the comparative evaluation also highlights the relative strengths of different algorithms with respect to the type of performance criteria, e.g., social welfare vs. attainment of equilibrium.
Teaching and Leading an Ad Hoc Teammate: Collaboration without Pre-Coordination
, 2013
"... As autonomous agents proliferate in the real world, both in software and robotic settings, they will increasingly need to band together for cooperative activities with previously unfamiliar teammates. In such ad hoc team settings, team strategies cannot be developed a priori. Rather, an agent must b ..."
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Cited by 5 (2 self)
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As autonomous agents proliferate in the real world, both in software and robotic settings, they will increasingly need to band together for cooperative activities with previously unfamiliar teammates. In such ad hoc team settings, team strategies cannot be developed a priori. Rather, an agent must be prepared to cooperate with many types of teammates: it must collaborate without pre-coordination. This article defines two aspects of collaboration in two-player teams, involving either simultaneous or sequential decision making. In both cases, the ad hoc agent is more knowledgeable of the environment, and attempts to influence the behavior of its teammate such that they will attain the optimal possible joint utility.
