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Katie Genter

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11 papers
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11

AAMAS Conference 2017 Conference Paper

Agent Behaviors for Joining and Leaving a Flock

  • Katie Genter
  • Peter Stone

Each individual bird in a flock of birds updates its behavior based on the behaviors of its neighbors. Previous work has considered how a small set of algorithmically controlled influencing agents, or robot birds, can influence the flock to behave in a particular way — such as to avoid airports or wind farms. These robot birds are assumed to be seen by the flock as ordinary birds, and hence are able to influence their neighbors. However, we are aware of no previous work that has considered the issues related to robot birds joining and leaving flocks of natural birds. Due to the influence the robot birds have on the flock as soon as members of the flock become neighbors, joining and leaving are not straightforward. In this abstract, we discuss simple approaches for robot birds to use when joining and leaving flocks of natural birds.

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AAMAS Conference 2017 Conference Paper

Three Years of the RoboCup Standard Platform League Drop-In Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition (JAAMAS Extended Abstract)

  • Katie Genter
  • Tim Laue
  • Peter Stone

The Standard Platform League is one of the main competitions at the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2013, the league began a new competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i. e. teams that consist of robots originating from different RoboCup teams and as such running different software. In the article advertised by this extended abstract, we provide an overview of this competition, including its motivation, rules, and how these rules have changed across three iterations of the competition. We also present and analyze the strategies utilized by various drop-in players as well as the results of the first three competitions. The article concludes by suggesting improvements for future competitive evaluations of ad hoc teamwork. To the best of our knowledge, the three Drop-in Player Competitions described in the article are the largest annual ad hoc teamwork robotic experiment to date. Across three years, the competition saw 56 entries from 30 different organizations and consisted of 510 minutes of game time that resulted in approximately 85 robot hours.

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AAMAS Conference 2016 Conference Paper

Adding Influencing Agents to a Flock

  • Katie Genter
  • Peter Stone

Many different animals, including birds and fish, exhibit a collective behavior known as flocking. Flocking behavior is believed by biologists to emerge from relatively simple local control rules utilized by each individual in a flock. Specifically, each individual adjusts its behavior based on the behaviors of its closest neighbors. In our work we consider the possibility of adding a small set of influencing agents, which are under our control, to a flock. Specifically, we advance existing work on adding influencing agents into a flock and begin to consider the case in which influencing agents must join a flock in motion. Following ad hoc teamwork methodology, we assume that we are given knowledge of, but no direct control over, the rest of the flock. As such, we use the influencing agents to alter the flock’s behavior — for example by encouraging all of the individuals to face the same direction or by altering the trajectory of the flock. In this paper we define several new methods for adding influencing agents into the flock and compare them against existing methods.

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JAAMAS Journal 2016 Journal Article

Three years of the RoboCup standard platform league drop-in player competition

  • Katie Genter
  • Tim Laue
  • Peter Stone

Abstract The Standard Platform League is one of the main competitions at the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2013, the league began a new competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i. e. teams that consist of robots originating from different RoboCup teams and as such running different software. In this article, we provide an overview of this competition, including its motivation, rules, and how these rules have changed across three iterations of the competition. We then present and analyze the strategies utilized by various drop-in players as well as the results of the first three competitions before suggesting improvements for future competitive evaluations of ad hoc teamwork. To the best of our knowledge, these three competitions are the largest annual ad hoc teamwork robotic experiment to date. Across three years, the competition has seen 56 entries from 30 different organizations and consisted of 510 min of game time that resulted in approximately 85 robot hours.

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IS Journal 2016 Journal Article

UT Austin Villa: Project-Driven Research in AI and Robotics

  • Katie Genter
  • Patrick MacAlpine
  • Jacob Menashe
  • Josiah Hannah
  • Elad Liebman
  • Sanmit Narvekar
  • Ruohan Zhang
  • Peter Stone

UT Austin Villa is a robot soccer team that has competed in the annual RoboCup soccer competitions since 2003. The team has won several championships and has inspired research contributions spanning many topics in robotics and artificial intelligence. This article summarizes some of these research contributions and provides a snapshot into the current development status of the team. Educational uses of the team's code bases are also presented.

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IROS Conference 2015 Conference Paper

Benchmarking robot cooperation without pre-coordination in the RoboCup Standard Platform League drop-in player competition

  • Katie Genter
  • Tim Laue 0001
  • Peter Stone 0001

The Standard Platform League is one of the main competitions of the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2014, the league added a new sub-competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i. e. teams that consist of robots originating from different RoboCup teams and that are each running different software. In this paper, we provide an overview of this competition, including its motivation and rules. We then present and analyze the results of the 2014 competition, which gathered robots from 23 teams, involved at least 50 human participants, and consisted of fifteen 20-minute games for a total playing time of 300 minutes. We also suggest improvements for future iterations, many of which will be evaluated at RoboCup 2015.

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AAAI Conference 2015 Conference Paper

Placing Influencing Agents in a Flock

  • Katie Genter
  • Peter Stone

Flocking is a emergent behavior exhibited by many different animal species, including birds and fish. In our work we consider adding a small set of influencing agents, that are under our control, into a flock. Following ad hoc teamwork methodology, we assume that we are given knowledge of, but no direct control over, the rest of the flock. In our ongoing work highlighted in this abstract, we are specifically considering the problem of where to initially place influencing agents that we add to such a flock. We use these influencing agents to influence the flock to behave in a particular way - for example, to fly in a particular orientation or fly in a particular pattern such as to avoid an obstacle.

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IROS Conference 2014 Conference Paper

The RoboCup 2013 drop-in player challenges: Experiments in ad hoc teamwork

  • Patrick MacAlpine
  • Katie Genter
  • Samuel Barrett
  • Peter Stone 0001

As the prevalence of autonomous agents grows, so does the number of interactions between these agents. Therefore, it is desirable for these agents to be capable of banding together with previously unknown teammates towards a common goal: to collaborate without pre-coordination. While past research on ad hoc teamwork has focused mainly on theoretical treatments and empirical studies in relatively simple domains, the long-term vision has been to enable robots and 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 introduces a series of pick-up robot soccer experiments that were carried out in three different leagues at the international RoboCup competition in 2013. In all cases, agents from different labs were put on teams with no pre-coordination. This paper introduces the structure of these experiments, describes the strategies used by UT Austin Villa in each challenge, and analyzes the results. The paper's main contribution is the introduction of a new large-scale ad hoc teamwork testbed that can serve as a starting point for future experimental ad hoc teamwork research.

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AAMAS Conference 2013 Conference Paper

Ad Hoc Teamwork for Leading a Flock

  • Katie Genter

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 my work I 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, I consider the problem of leading a flock of agents to some desired behavior using a subset of the flock that is comprised of ad hoc agents. I consider this problem not only theoretically, but also in a custom-designed simulator FlockSim.

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AAMAS Conference 2012 Conference Paper

Role Selection in Ad Hoc Teamwork

  • Katie Genter
  • Noa Agmon
  • Peter Stone

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 work we introduce 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 other team members. We present methods for evaluating the influence of the ad hoc agent’s role selection on the team’s utility and we examine empirically how to choose the best suited method for role assignment in a complex environment. Finally, we show that an appropriate assignment method can be determined from a limited amount of data and used successfully in new tasks that the team has not encountered before.

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AAAI Conference 2011 Conference Paper

Role-Based Ad Hoc Teamwork

  • Katie Genter
  • Noa Agmon
  • Peter Stone

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 abstract 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 present methods for evaluating the influence of the ad hoc agent’s role selection on the team’s utility and we examine empirically how to select the best suited method for role assignment in a complex environment. Finally, we show that an appropriate assignment method can be determined from a limited amount of data and used successfully in similar new tasks that the team has not encountered before.

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