Characterization of Optimal Strategies in Dynamic Games

1982 ◽  
Vol 33 (5) ◽  
pp. 496-497
Author(s):  
Lyn Thomas
Keyword(s):  
Dynamic Games ◽  
Optimal Strategies

Characterization of Optimal Strategies in Dynamic Games

1982 ◽  
Vol 33 (5) ◽  
pp. 496
Author(s):  
Lyn Thomas ◽  
L. P. J. Groenwegen
Keyword(s):  
Dynamic Games ◽  
Optimal Strategies

scholarly journals A Stochastic Characterization of the Capture Zone in Pursuit-Evasion Games

Games ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 54
Author(s):  
Simone Battistini
Keyword(s):  
Optimal Strategies ◽  
Capture Zone ◽  
Pursuit Evasion ◽  
Guidance Strategies ◽  
Stochastic Characterization ◽  
Evasion Game ◽  
Multi Agent ◽  
Planning Problems ◽  
Insight Into

Pursuit-evasion games are used to define guidance strategies for multi-agent planning problems. Although optimal strategies exist for deterministic scenarios, in the case when information about the opponent players is imperfect, it is important to evaluate the effect of uncertainties on the estimated variables. This paper proposes a method to characterize the game space of a pursuit-evasion game under a stochastic perspective. The Mahalanobis distance is used as a metric to determine the levels of confidence in the estimation of the Zero Effort Miss across the capture zone. This information can be used to gain an insight into the guidance strategy. A simulation is carried out to provide numerical results.

A Stochastic Model for Service Contract

1998 ◽  
Vol 05 (01) ◽  
pp. 29-45 ◽  
Author(s):  
D. N. P. Murthy ◽  
E. Asgharizadeh
Keyword(s):  
Sensitivity Analysis ◽  
Simple Model ◽  
Single Agent ◽  
Optimal Strategies ◽  
Complete Characterization ◽  
Viable Option ◽  
Service Contract ◽  
External Agent ◽  
Maintenance Service

When it is not economical to carry out maintenance in-house, out-sourcing to an external agent is an alternate viable option. In this paper, we study a simple maintenance service contract involving a single agent (providing the maintenance service) and a single customer (owner of the equipment and recipient of the maintenance service). We develop a simple model to obtain the optimal strategies for both the customer and the agent. We give a complete characterization of the strategies along with some sensitivity analysis and discuss some extensions.

scholarly journals Characterization and simplification of optimal strategies in positive stochastic games

2018 ◽  
Vol 55 (3) ◽  
pp. 728-741 ◽  
Author(s):  
János Flesch ◽  
Arkadi Predtetchinski ◽  
William Sudderth
Keyword(s):  
State Space ◽  
Optimal Strategy ◽  
Stochastic Games ◽  
Optimal Strategies ◽  
Action Space ◽  
Positive Zero ◽  
Countable State ◽  
Zero Sum ◽  
Action Spaces

Abstract We consider positive zero-sum stochastic games with countable state and action spaces. For each player, we provide a characterization of those strategies that are optimal in every subgame. These characterizations are used to prove two simplification results. We show that if player 2 has an optimal strategy then he/she also has a stationary optimal strategy, and prove the same for player 1 under the assumption that the state space and player 2's action space are finite.

scholarly journals On the Dubins and Savage Characterization of Optimal Strategies

1972 ◽  
Vol 43 (2) ◽  
pp. 498-507 ◽  
Author(s):  
William D. Sudderth
Keyword(s):  
Optimal Strategies

COARSE-GRAINED PARALLELIZATION OF THE ADVANCED NEUROSIMULATOR FAUN 1.0 WITH PVM AND THE ENHANCED CORNERED RAT GAME REVISITED

2005 ◽  
Vol 07 (03) ◽  
pp. 347-365 ◽  
Author(s):  
HANS-JÖRG VON METTENHEIM ◽  
MICHAEL H. BREITNER
Keyword(s):  
High Performance ◽  
Dynamic Games ◽  
Optimal Strategies ◽  
General Purpose ◽  
Open Loop ◽  
The State ◽  
Coarse Grained ◽  
State Variables ◽  
Advantages And Disadvantages ◽  
Game Modification

Today artificial neural networks are very useful to solve complex dynamic games of various types, i.e., to approximate optimal strategies with sufficient accuracy. Exemplarily four synthesis approaches for the solution of zero-sum, noncooperative dynamic games are outlined and discussed. Either value function, adjoint vector components or optimal strategies can be synthesized as functions of the state variables. In principle all approaches enable the solution of dynamic games. Nevertheless every approach has advantages and disadvantages which are discussed. The neural network training usually is very difficult and computationally very expensive. The coarse-grained parallelization FAUN 1.0-HPC-PVM of the advanced neurosimulator FAUN uses PVM subroutines and runs on heterogeneous and decentralized networks interconnecting general-purpose workstations, PCs and also high-performance computers. Computing times of days, weeks or months can be cut down to hours. An enhanced cornered rat game — formulated and analyzed in 1993 — serves as an example. Optimal strategies for cat and rat are synthesized. For this purpose open-loop representations of optimal strategies on an equidistant grid in the state space are used. An important end game modification is presented.

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