Resolving Conflicts in Highly Reactive Teams

In distributed cooperation frameworks for completely autonomous agents, conflicts between the involved agents can occur due to inconsistent data available to the agents. In highly dynamic domains, such as RoboCup, it is often neccessary to accept a certain level of conflicts in order to decrease reaction time of single agents, instead of relying on error-free, but extensive communication. However, this may lead to situations in which unresolved conflicts linger and cause cooperation to break down completely. In our cooperation framework, ALICA, we designed and implemented a simple but effective approach to detect these cases and resolve them quickly through a bully algorithm

Strategy learning for reasoning agents

Abstract. We present a method for knowledge-based agents to learn strategies. Using techniques of inductive logic programming, strategies are learned in two steps: A given example set is first generalized into an overly general theory, which then gets refined. We show how a learning agent can exploit background knowledge of its actions and environment in order to restrict the hypothesis space, which enables the learning of complex logic program clauses. This is a first step toward the long term goal of adaptive, reasoning agents capable of changing their behavior when appropriate.

Using Incomplete Satisfiability Modulo Theories to Determine Robotic Tasks*

Abstract-Many robotic task specifications can be naturally expressed by boolean combinations of arbitrary constraints. This allows a separation of problem description and solution strategy. In this paper, we present a novel approach to solve non-linear constraint systems based on Satisfiability Modulo Theories. While most SMT-based techniques emphasize completeness, we intentionally use an incomplete local search strategy. Despite this incompleteness, the presented solution is able to deal with many real world problems like task allocation or robot positioning. We show that our approach is able to exploit the logical structure to solve highly complex tasks almost in real-time