Negative Reinforcement and Backtrack-Points for Recurrent Neural Networks for Cost-Based Abduction

Abduction is the process of proceeding from data describing a set of observations or events, to a set of hypotheses which best explains or accounts for the data. Cost-based abduction (CKA) is an AI formalism in which evidence to be explained is treated as a goal to be proven, proofs have costs based on how much needs to be assumed to complete the proof, and the set of assumptions needed to complete the least-cost proof are taken as the best explanation for the given evidence. In this paper, we introduce two techniques for improving the performance of high order recurrent networks (HORN) applied to cost-based abduction. In the backtrack-points technique, we use heuristics to recognize early that the network trajectory is moving in the wrong direction; we then restore the network state to a previously-stored point, and apply heuristic perturbations to nudge the network trajectory in a different direction. In the negative reinforcement technique, we add hyperedges to the network to reduce the attractiveness of local-minima. We apply these techniques on a 300-hypothesis, 900-rule particularly-difficult instance of CBA

Complexity of Discrete Energy Minimization Problems

Discrete energy minimization is widely-used in computer vision and machine learning for problems such as MAP inference in graphical models. The problem, in general, is notoriously intractable, and finding the global optimal solution is known to be NP-hard. However, is it possible to approximate this problem with a reasonable ratio bound on the solution quality in polynomial time? We show in this paper that the answer is no. Specifically, we show that general energy minimization, even in the 2-label pairwise case, and planar energy minimization with three or more labels are exp-APX-complete. This finding rules out the existence of any approximation algorithm with a sub-exponential approximation ratio in the input size for these two problems, including constant factor approximations. Moreover, we collect and review the computational complexity of several subclass problems and arrange them on a complexity scale consisting of three major complexity classes -- PO, APX, and exp-APX, corresponding to problems that are solvable, approximable, and inapproximable in polynomial time. Problems in the first two complexity classes can serve as alternative tractable formulations to the inapproximable ones. This paper can help vision researchers to select an appropriate model for an application or guide them in designing new algorithms.Comment: ECCV'16 accepte

Utilizing multiple pheromones in an ant-based algorithm for continuous-attribute classification rule discovery.

The cAnt-Miner algorithm is an Ant Colony Optimization (ACO) based technique for classification rule discovery in problem domains which include continuous attributes. In this paper, we propose several extensions to cAnt- Miner. The main extension is based on the use of multiple pheromone types, one for each class value to be predicted. In the proposed ?cAnt-Miner algorithm, an ant first selects a class value to be the consequent of a rule and the terms in the antecedent are selected based on the pheromone levels of the selected class value; pheromone update occurs on the corresponding pheromone type of the class value. The pre-selection of a class value also allows the use of more precise measures for the heuristic function and the dynamic discretization of continuous attributes, and further allows for the use of a rule quality measure that directly takes into account the confidence of the rule. Experimental results on 20 benchmark datasets show that our proposed extension improves classification accuracy to a statistically significant extent compared to cAnt-Miner, and has classification accuracy similar to the well-known Ripper and PART rule induction algorithms

Speed control of BLDC motor by using PID control and self-tuning fuzzy PID controller

This paper presents three different robust controller techniques for high performance brushless DC (BLDC) motor. The purpose is to test the ability of each control technique to force the rotor to follow a preselected speed/position track. This objective should be achieved regardless the parameter variations, and external disturbances. The first technique is conventional PID controller. The second controller technique use genetic algorithm to adjust the PID controller parameters based on three different cost functions. Finally a self-tuning fuzzy PID controller is developed and tested. These controllers are tested for both speed regulation and speed tracking. Results shows that the proposed self-tuning fuzzy PID controller has better performance

Comparative anatomical studies on some species of the genus Amaranthus (Family: Amaranthaceae) for the development of an identification guide

A study of anatomical features of mature leaves and stems (at fruiting stage) of 12 Amaranthus taxa (Family: Amaranthaceae) shows high variation between them and supplied new characters. The internal structures were evaluated to clarify their effectiveness in solving taxonomic complexity and identification difficulty in this genus. Observation of the transections of blades showed that the epidermis is uniseriate, ground tissue consists of angular collenchyma and thin parenchyma. The vascular bundles shape has three patterns crescent, ring, ovate. Also they may be united or separated while the midrib shape in cross section has two patterns in which U-shaped, cordate or crescent bundle occurs. All leaves are petiolate. The examination of the petioles exhibits new and varied characters such as petiole shape (cross section), vascular bundles (shape, number, arrangement). While the resulted characters from the observation of the stem structure showed less variation. Nineteen qualitative characters with 38 character states resulted from leaf anatomy. Only (8) characters were sufficient to generate an identification anatomical key. DELTA program was used in key-generation. Also different measurements were carried out by a photo analysis program (Image J), such as lamina thickness, mesophyll thickness, area of upper and lower epidermal cells and thickness of upper and lower epidermal cells to exhibit most possible dissimilarities between the studied species