An Analysis of Derived Belief Strategy’s Performance in the 2005 Iterated Prisoner’s Dilemma Competition

This report analyze the performance of the Derived Belief Strategy (DBS) in the 2005 Iterated Prisoner’s Dilemma Competition [1]. Our technique is to remove the participants from the computation of the average scores, as if they have never participated in the competition

Synthesis of Strategies for Non-Zero-Sum Repeated Games

There are numerous applications that involve two or more self-interested autonomous agents that repeatedly interact with each other in order to achieve a goal or maximize their utilities. This dissertation focuses on the problem of how to identify and exploit useful structures in agents' behavior for the construction of good strategies for agents in multi-agent environments, particularly non-zero-sum repeated games. This dissertation makes four contributions to the study of this problem. First, this thesis describes a way to take a set of interaction traces produced by different pairs of players in a two-player repeated game, and then find the best way to combine them into a strategy. The strategy can then be incorporated into an existing agent, as an enhancement of the agent's original strategy. In cross-validated experiments involving 126 agents for the Iterated Prisoner's Dilemma, Iterated Chicken Game, and Iterated Battle of the Sexes, my technique was able to make improvement to the performance of nearly all of the agents. Second, this thesis investigates the issue of uncertainty about goals when a goal-based agent situated in a nondeterministic environment. The results of this investigation include the necessary and sufficiency conditions for such guarantee, and an algorithm for synthesizing a strategy from interaction traces that maximizes the probability of success of an agent even when no strategy can assure the success of the agent. Third, this thesis introduces a technique, Symbolic Noise Detection (SND), for detecting noise (i.e., mistakes or miscommunications) among agents in repeated games. The idea is that if we can build a model of the other agent's behavior, we can use this model to detect and correct actions that have been affected by noise. In the 20th Anniversary Iterated Prisoner's Dilemma competition, the SND agent placed third in the "noise" category, and was the best performer among programs that had no "slave" programs feeding points to them. Fourth, the thesis presents a generalization of SND that can be wrapped around any existing strategy. Finally, the thesis includes a general framework for synthesizing strategies from experience for repeated games in both noisy and noisy-free environments

SHOP2: An HTN planning system

The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning domains.open17833

Reactive query policies: A formalism for planning with volatile external information

Abstract — To generate plans for collecting data for data mining, an important problem is information volatility during planning: the information needed by the planning system may change or expire during the planning process, as changes occur in the data being collected. In such situations, the planning system faces two challenges: how to generate plans despite these changes, and how to guarantee that a plan returned by the planner will remain valid for some period of time after the planning ends. The focus of our work is to address both of the above challenges. In particular, we provide: 1) A formalism for reactive query policies, a class of strategies for deciding when to reissue queries for information that has changed during the planning process. This class includes all query management strategies that have yet been developed. 2) A new reactive query policy called the presumptive strategy. In our experiments, the presumptive strategy ran exponentially faster than the lazy strategy, the best previously known query management strategy. In the hardest set of problems we tested, the presumptive strategy took 4.7 % as much time and generated 6.9 % as many queries as the lazy strategy. I

Gridlock-free Autonomous Parking Lots for Autonomous Vehicles

Many cities suffer from a shortage of parking spaces. Research in high density parking (HDP) focuses on how to increase the capacity of parking lots by allowing vehicles to block each other but temporarily give way to other vehicles by driving autonomously upon request. Previous works on HDP did not consider mixing different parking strategies and ignored the possibility of gridlock when multiple vehicles move simultaneously. In this paper, we describe the design of autonomous parking lots, which allows the deployment of different parking strategies in different regions in a parking lot. We present algorithms for checking whether adding a vehicle to an autonomous parking lot can lead to gridlock. Our simulation shows that autonomous parking lots can hold 60% more vehicles given the same amount of space