English
Related papers

Related papers: GIST: A Solver for Probabilistic Games

200 papers

Gradient Descent (GD) is a ubiquitous algorithm for finding the optimal solution to an optimization problem. For reduced computational complexity, the optimal solution $\mathrm{x^*}$ of the optimization problem must be attained in a minimum…

Optimization and Control · Mathematics 2023-06-01 Revati Gunjal , Sushama Wagh , Syed Shadab Nayyer , Alex Stankovic , Navdeep M. Singh

This short note is devoted to the unraveling of the hidden interactivity of ordinary games which is an artefact of predictions of the behaviour of other players by the fixed player and describes deviations of their real behaviour from such…

Optimization and Control · Mathematics 2007-05-23 Denis V. Juriev

Zero-sum stochastic games are easy to solve as they can be cast as simple Markov decision processes. This is however not the case with general-sum stochastic games. A fairly general optimization problem formulation is available for…

Machine Learning · Computer Science 2015-07-02 H. L. Prasad , Shalabh Bhatnagar

Playing text-based games requires skills in processing natural language and sequential decision making. Achieving human-level performance on text-based games remains an open challenge, and prior research has largely relied on hand-crafted…

The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in game-oriented research and industry. A special class of these…

Artificial Intelligence · Computer Science 2023-02-17 Vanessa Volz , Boris Naujoks , Pascal Kerschke , Tea Tusar

Generating tests for games is challenging due to the high degree of randomisation inherent to games and hard-to-reach program states that require sophisticated gameplay. The test generator NEATEST tackles these challenges by combining…

Software Engineering · Computer Science 2025-01-15 Patric Feldmeier , Katrin Schmelz , Gordon Fraser

We present a new model of incomplete information games without private information in which the players use a distributionally robust optimization approach to cope with the payoff uncertainty. With some specific restrictions, we show that…

Computer Science and Game Theory · Computer Science 2016-10-04 Nicolas Loizou

Quantum impurity solvers have a broad range of applications in theoretical studies of strongly correlated electron systems. Especially, they play a key role in dynamical mean-field theory calculations of correlated lattice models and…

Strongly Correlated Electrons · Physics 2015-06-23 Li Huang , Yilin Wang , Zi Yang Meng , Liang Du , Philipp Werner , Xi Dai

FISTA is a popular convex optimisation algorithm which is known to converge at an optimal rate whenever a minimiser is contained in a suitable Hilbert space. We propose a modified algorithm where each iteration is performed in a subset…

Optimization and Control · Mathematics 2022-10-06 Antonin Chambolle , Robert Tovey

Tasks of different nature and difficulty levels are a part of people's lives. In this context, there is a scientific interest in the relationship between the difficulty of the task and the persistence need to accomplish it. Despite the…

Human-Computer Interaction · Computer Science 2024-04-25 Leonardo Ribeiro da Cunha , Leonardo Oliveira Mendes , Renio dos Santos Mendes

In this paper, we present a method and a tool to build symbolic labelled transition systems from B specifications. The tool, called GeneSyst, can take into account refinement levels and can visualize the decomposition of abstract states in…

Logic in Computer Science · Computer Science 2010-04-12 Didier Bert , Marie-Laure Potet , Nicolas Stouls

Underlying relationships among Multi-Agent Systems (MAS) in hazardous scenarios can be represented as Game-theoretic models. This paper proposes a new hierarchical network-based model called Game-theoretic Utility Tree (GUT), which…

Multiagent Systems · Computer Science 2023-03-30 Qin Yang , Ramviyas Parasuraman

While discounted payoff games and classic games that reduce to them, like parity and mean-payoff games, are symmetric, their solutions are not. We have taken a fresh view on the constraints that optimal solutions need to satisfy, and…

Data Structures and Algorithms · Computer Science 2023-10-03 Daniele Dell'Erba , Arthur Dumas , Sven Schewe

This work presents a novel policy iteration algorithm to tackle nonzero-sum stochastic impulse games arising naturally in many applications. Despite the obvious impact of solving such problems, there are no suitable numerical methods…

Optimization and Control · Mathematics 2020-06-29 René Aïd , Francisco Bernal , Mohamed Mnif , Diego Zabaljauregui , Jorge P. Zubelli

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural…

Computer Science and Game Theory · Computer Science 2021-09-20 Tobias Winkler , Maximilian Weininger

Under the assumptions that (i) gamification consists of various types of users that experience game design elements differently; and (ii) gamification is deployed in order to achieve some goal in the broadest sense, we pose the gamification…

Human-Computer Interaction · Computer Science 2014-07-04 Michael Meder , Brijnesh-Johannes Jain

We develop an Integral Transformation Method (ITM) for the study of suitable optimal control and differential game models. This allows for a solution to such dynamic problems to be found through solving a family of optimization problems…

Theoretical Economics · Economics 2025-01-06 Raouf Boucekkine , Giorgio Fabbri , Salvatore Federico , Fausto Gozzi , Ted Loch-Temzelides , Cristiano Ricci

Parity games have important practical applications in formal verification and synthesis, especially to solve the model-checking problem of the modal mu-calculus. They are also interesting from the theory perspective, as they are widely…

Logic in Computer Science · Computer Science 2018-07-30 Tom van Dijk

We introduce Generalized Integrated Gradients (GIG), a formal extension of the Integrated Gradients (IG) (Sundararajan et al., 2017) method for attributing credit to the input variables of a predictive model. GIG improves IG by explaining a…

Machine Learning · Computer Science 2019-09-10 John Merrill , Geoff Ward , Sean Kamkar , Jay Budzik , Douglas Merrill

In recent years, there has been a growing interest in games on graphs within the research community, fueled by their relevance in applications such as economics, politics, and epidemiology. This paper aims to comprehensively detail the…

Computer Science and Game Theory · Computer Science 2024-06-11 Christian Giannetti