Unmanned Vehicle Operations: Countering Imperfect Information in an Adversarial Environment

McEneaney, William M.; Singh, Rajdeep

doi:10.2514/6.2004-6411

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…In this work, given any Blue control strategy which employs the conditional probability distribution as the basis for control actions, one can compute a Red controller to exploit the Blue controller. Further work will develop the theory for computation of the maximin Red controller against all Blue control strategies based on the conditional probability and consideration of approaches for Blue such as that of [8], [9], [12]. Note that the even in the finite state space case there are computational issues; the appended state (now including the conditional distribution) is a function over a simplex of dimension R n (if state space is size n).…”

Section: Imperfect Information Game (Iig)mentioning

confidence: 99%

“…The result is an algoritm which will produce "deceptive" controls (when appropriate) under the assumption of this Blue opponent. An open question is whether (and under what conditions), this approach yields superior performance for Red as compared with state feedback when Blue may apply not only the above approach , but also the new theory of [8], [9], [12] as well.The theory will be generalized to a more complex Blue player structure.…”

Section: Introductionmentioning

confidence: 96%

“…In particular, we concentrate on a simple (sub)class of discrete-time/discretespace stochastic games where the Red player has perfect information, and the Blue player must base his control on a noise-corrupted observation process. An information state and corresponding certainty equivalence theorem have been obtained for this problem under a saddle-point condition [8], [9], [12].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exploitation of an opponent's imperfect information in a stochastic game with autonomous vehicle application

McEneaney

Singh²

2004

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)

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We consider a finite state space, discrete stochastic game problem where only one player has perfect information. In the notation employed here only the "Red" player has the perfect state information. The "Blue" player only has access to observation-based information. To some degree the observations may be influenced by the controls of both players. A Markov chain model is used where the transition probabilities depend on the controls of the players. The game is zero-sum. It is known that application of the optimal control at a maximum likelihood estimate by the Blue player is not optimal; under a saddle point condition, a form of Certainty Equivalence does exist for the Blue player, but the structure is more complex than the above approach. In this work, the point of view of the Red player is considered. Simulation is used to demonstrate that the optimal state feedback control for Red is not the optimal control (even with perfect information for Red). This is a significantly stronger statement than that Certainty Equivalence does not hold when the Red player has imperfect information. A theory for the development of Red control is presented. This yields "deceptive" controls in the presence of the simpler Blue approach above, which provide superior performance in this case. An open question is whether (and under what conditions), this approach yields superior performance for Red as compared with state feedback when Blue is allowed strategies including the more complex one above. Experimentation and theory will be employed to answer this question.

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Section: Imperfect Information Game (Iig)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploitation of an opponent's imperfect information in a stochastic game with autonomous vehicle application

McEneaney

Singh²

2004

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)

View full text Add to dashboard Cite

show abstract

“…Qualitatively and descriptively, deception has been studied in military domains [1] and in interpersonal cheating [5]. Handling of incomplete, potentially erroneous, and intentionally distorted information has been studied in control theory and game theory, e.g., [6,7].…”

Section: Introduction and Contextmentioning

confidence: 99%