Cooperative Epistemic Multi-Agent Planning for Implicit Coordination

Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Recently, Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. We extend the DEL-based epistemic planning framework to include perspective shifts, allowing us to define new notions of sequential and conditional planning with implicit coordination. With these, it is possible to solve planning tasks with joint goals in a decentralized manner without the agents having to negotiate about and commit to a joint policy at plan time. First we define the central planning notions and sketch the implementation of a planning system built on those notions. Afterwards we provide some case studies in order to evaluate the planner empirically and to show that the concept is useful for multi-agent systems in practice.Comment: In Proceedings M4M9 2017, arXiv:1703.0173

Класифікація способів покращення пошуку по дереву методом Монте-Карло, орієнтованих на особливості цього методу

У статті, на основі інформації з різних джерел про пошук по дереву методом Монте-Карло (MCTS), пропонується уточнена структура класифікації та перша версія класифікації способів покращення базової реалізації методу MCTS. У цій версії, на даний момент, розглянуті тільки суто теоретичні способи покращення етапів загальної схеми MCTS, які орієнтовані на особливості роботи цього методу. Передбачається, що запропонована класифікація може бути в подальшому розширена і використана для систематизації знань про метод MCTS та виявлення нових можливостей його покращення.In the article basing on information taken from various sources about Monte-Carlo tree search (MCTS) method, the updated structure of classification and the first version of just the classification of improvement techniques of the basic MCTS method implementation are proposed. For the moment, this version of the classification discusses only pure theoretical techniques for improving of steps of the general MCTS schema, which are oriented to specifics of the method. It is supposed that the proposed classification can be used for systematization of knowledge about MCTS method and discovering of new possibilities for its improvement

Oncostatin M induces heat hypersensitivity by gp130-dependent sensitization of TRPV1 in sensory neurons

Oncostatin M (OSM) is a member of the interleukin-6 cytokine family and regulates eg. gene activation, cell survival, proliferation and differentiation. OSM binds to a receptor complex consisting of the ubiquitously expressed signal transducer gp130 and the ligand binding OSM receptor subunit, which is expressed on a specific subset of primary afferent neurons. In the present study, the effect of OSM on heat nociception was investigated in nociceptor-specific gp130 knock-out (SNS-gp130-/-) and gp130 floxed (gp130fl/fl) mice

A Planning-based Approach for Music Composition

. Automatic music composition is a fascinating field within computational creativity. While different Artificial Intelligence techniques have been used for tackling this task, Planning – an approach for solving complex combinatorial problems which can count on a large number of high-performance systems and an expressive language for describing problems – has never been exploited. In this paper, we propose two different techniques that rely on automated planning for generating musical structures. The structures are then filled from the bottom with “raw” musical materials, and turned into melodies. Music experts evaluated the creative output of the system, acknowledging an overall human-enjoyable trait of the melodies produced, which showed a solid hierarchical structure and a strong musical directionality. The techniques proposed not only have high relevance for the musical domain, but also suggest unexplored ways of using planning for dealing with non-deterministic creative domains

Cost-Sensitive Concurrent Planning Under Duration Uncertainty for Service-Level Agreements

This paper brings together work in stochastic modelling, using the process algebra PEPA, and work in automated planning. Stochastic modelling has been concerned with verification of system performance metrics for some time: given a model of a system, determining whether it will meet a service-level agreement (SLA). For example, whether a given sequence of transitions on a network will complete within 5 seconds 80% of the time. The problem of deciding how to reconfigure the system most cost-effectively when the SLA cannot be met has not been widely explored: it is currently solved manually. Inspired by this, we consider how planning can be used to automate the configuration of service-oriented systems. Configuring these stochastic systems presents new challenges to planning: building plans that meet SLAs, but also have low cost. To this end, we present a domain-independent planner for planning problems with action costs and stochastic durations, and show how this can be used to solve both traditional planning domains, and within the framework of configuring a larger process algebra model