Results

**1 - 8**of**8**### Hybrid Multiagent Systems with Timed Synchronization – Specification and Model Checking

, 2007

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### Probability Propagation in Petri Nets

, 2005

"... A class of high level Petri nets, called ”probability propagation nets”, is introduced which is particularly useful for modelling probability and evidence propagation. It is demonstrated how propagation of probabilistic Horn abduction and Bayesian networks can be represented and structured by these ..."

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A class of high level Petri nets, called ”probability propagation nets”, is introduced which is particularly useful for modelling probability and evidence propagation. It is demonstrated how propagation of probabilistic Horn abduction and Bayesian networks can be represented and structured by these nets. Their simplest form is a probabilistic extension of place/transition nets for modelling logical formulae and deductions. As a consequence, the main means for structuring are transition invariants that can easily be calculated for all ”probability propagation nets” on a place/transition net level.

### Some Examples of Semi-rational and Non-semi-rational DAG Languages. Extended Version

"... The class of semi-rational dag (d irected acyclic graph) languages can be equivalently characterized by labeled Petri nets with ε-transitions, by rather simple leave substituting tree grammars with additional non-local merge rules, or as a synchronization closure of Courcelles class of recognizable ..."

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The class of semi-rational dag (d irected acyclic graph) languages can be equivalently characterized by labeled Petri nets with ε-transitions, by rather simple leave substituting tree grammars with additional non-local merge rules, or as a synchronization closure of Courcelles class of recognizable sets of unranked, unordered trees. However, no direct recognition by some magma is known. For a better understanding, we present here some examples of languages within and without the class of semi-rational dag languages. 1

### Bayesian Networks and Petri Nets

"... Abstract A class of high level Petri nets, called ”probability propagation nets”, is introduced which is particularly useful for modeling probability and evidence propagation. These nets themselves are well suited to represent the probabilistic Horn abduction, whereas a specific folding of them will ..."

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Abstract A class of high level Petri nets, called ”probability propagation nets”, is introduced which is particularly useful for modeling probability and evidence propagation. These nets themselves are well suited to represent the probabilistic Horn abduction, whereas a specific folding of them will be used for representing the flows of probabilities and likelihoods in Bayesian networks. 1

### Rescue Analyzer – Extracting Agent Plans from Observation (Tool Description)

"... Abstract. One interesting area of research within multiagent systems is the recognition of agent plans by observation. Rescue Analyzer is a tool for analyzing logs from the RoboCup Rescue Simulation and for matching observations to a set of pre-specified plans. This allows for debugging of rescue ag ..."

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Abstract. One interesting area of research within multiagent systems is the recognition of agent plans by observation. Rescue Analyzer is a tool for analyzing logs from the RoboCup Rescue Simulation and for matching observations to a set of pre-specified plans. This allows for debugging of rescue agents as well as interesing extensions to the rescue competition itself. 1

### Implicit Coordination with Shared Belief: A Heterogeneous Robot Soccer Team Case Study

, 2009

"... A striking aspect of human coordination is that we achieve it with little or no communication. We achieve this implicit coordination by taking the perspective of others and inferring their intentions. In contrast, robots usually coordinate explicitly through the extensive communication of utilities ..."

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A striking aspect of human coordination is that we achieve it with little or no communication. We achieve this implicit coordination by taking the perspective of others and inferring their intentions. In contrast, robots usually coordinate explicitly through the extensive communication of utilities or intentions. In this paper we present a method that combines both approaches: implicit coordination with shared belief. In this approach, robots first communicate their beliefs about the world state to each other, using a CORBAbased communication module. They then use learned utility prediction models to predict the utility of each robot locally. Based on these utilities, an action is chosen. Within a heterogeneous soccer team, with robots from both the Munich and Ulm research groups, we apply implicit coordination with shared belief to a typical task from robotic soccer: regaining ball possession. An empirical evaluation demonstrates that the redundancy of implicit coordination with shared belief leads to robustness against communication failure and state estimation inaccuracy.

### Using CLP to Model Hybrid Systems

"... Abstract. Hybrid systems are the result of merging the two most commonly used models of dynamical systems, namely continuous dynamical systems defined by differential equations, and discrete event systems defined by automata. One can view hybrid systems as constrained systems. The constraints are us ..."

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Abstract. Hybrid systems are the result of merging the two most commonly used models of dynamical systems, namely continuous dynamical systems defined by differential equations, and discrete event systems defined by automata. One can view hybrid systems as constrained systems. The constraints are used to describe the possible flows, invariants and transitions on one hand, and to mark certain parts of the state space (e.g. the set of initial states, or the set of unsafe state) on the other hand. Therefore, it is natural to use Constraint Logic Programming (CLP) as an approach to model hybrid systems. One advantage from this approach is that the problem of analyzing hybrid systems can be solved by execution of the corresponding clp programs. This paper uses clp to model hybrid concurrent systems. This is possible by controlling the execution of the concurrent hybrid systems using time constraints of events.