Ole-Christoffer Granmo

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There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the second involves discretizing the probability space in which the LA operates. This paper demonstrates how both of these can be(More)
Stochastic point location (SPL) deals with the problem of a learning mechanism (LM) determining the optimal point on the line when the only input it receives are stochastic signals about the direction in which it should move. One can differentiate the SPL from the traditional class of optimization problems by the fact that the former considers the case(More)
The two-armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and(More)
In this paper, we propose a novel solution to the problem of identifying services of high quality. The reported solutions to this problem have, in one way or the other, resorted to using so-called “Reputation Systems” (RSs). Although these systems can offer generic recommendations by aggregating user-provided opinions about the quality of the services under(More)
In a multitude of real-world situations, resources must be allocated based on incomplete and noisy information. However, in many cases, incomplete and noisy information render traditional resource allocation techniques ineffective. The decentralized Learning Automata Knapsack Game (LAKG) was recently proposed for solving one such class of problems, namely(More)
This paper presents an efficient adaptive online routing algorithm for the computation of bandwidth-guaranteed paths in multiprotocol label switching witching (MPLS)-based networks by using a learning scheme that computes an optimal ordering of routes. The contribution of this work is twofold. The first is that we propose a new class of solutions other than(More)
The Goore Game (GG) introduced by M. L. Tsetlin in 1973 has the fascinating property that it can be resolved in a completely distributed manner with no intercommunication between the players. The game has recently found applications in many domains, including the field of sensor networks and quality-of-service (QoS) routing. In actual implementations of the(More)
We consider the problem of a user operating within a Cognitive Radio Network (CRN) which involves N channels each associated with a Primary User (PU). The problem consists of allocating a channel which, at any given time instant is not being used by a PU, to a Secondary User (SU). Within our study, we assume that a SU is allowed to perform “channel(More)