Job Shop Scheduling Problem (JSSP) is among the combinatorial optimization and Non-Deterministic Polynomial-time (NP) problems. Researchers have contributed to this area using several methods. Among them, we cite machine learning algorithms, more precisely Reinforcement Learning (RL). This algorithm suitable for discussed problem as agents can learn decisions optimize them according environment...

The applicability or terminating condition for the ordinary case of Zeilberger’s algorithm was recently obtained by Abramov. For the qanalogue, the question of whether a bivariate q-hypergeometric term has a qZ-pair remains open. Le has found a solution to this problem when the given bivariate q-hypergeometric term is a rational function in certain powers of q. We solve the problem for the gene...

We now look at the list decoding algorithm in the breakthrough work of Sudan [2]. To motivate the algorithm, recall that in the previous algorithm, in order to prove that Step 2 works, we defined a polynomial R(X) △ = Q(X,P (X)). In particular, this implied that deg(R) ≤ degX(Q) + k · degY (Q) (and we had to set t > degX(Q) + k · degY (Q)). One shortcoming of this approach is that the maximum d...

In this paper we present some notes of the PageRank algorithm, including its L1 condition number and some observation of the numerical tests of two variant algorithms which are based on the extrapolation method. 2005 Elsevier Inc. All rights reserved.

In some stochastic environments the well-known reinforcement learning algorithm Q-learning performs very poorly. This poor performance is caused by large overestimations of action values. These overestimations result from a positive bias that is introduced because Q-learning uses the maximum action value as an approximation for the maximum expected action value. We introduce an alternative way ...

This paper suggests a routing method for automated guided vehicles (AGVs) in port terminals by using a Q-learning technique. One of the important issues for the efficient operation of automated guided vehicle system (AGVS) is to find the shortest time route instead of the shortest distance route which is usually being used in practice. For the estimation of the travel time, the waiting time mus...

belief-network inference Adnan Darwiche and Gregory Provan Rockwell Science Center 1049 Camino Dos Rios Thousand Oaks, CA 91360 fdarwiche, [email protected] Abstract We describe a new paradigm for implementing inference in belief networks, which consists of two steps: (1) compiling a belief network into an arithmetic expression called a Query DAG (Q-DAG); and (2) answering queries using...

Wireless networks are increasingly overwhelmed by Distributed Denial of Service (DDoS) attacks by generating flooding packets that exhaust critical computing and communication resources of a victim’s mobile device within a very short period of time. This must be protected. Effective detection of DDoS attacks requires an adaptive learning classifier, with less computational complexity, and an ac...

This paper presents a hexagon-based Q-leaning algorithm to find a hidden target object with multiple robots. An experimental environment was designed with five small mobile robots, obstacles, and a target object. Robots went in search of a target object while navigating in a hallway where obstacles were strategically placed. This experiment employed two control algorithms: an area-based action ...