ACRIPPER: A New Associative Classification Based on RIPPER Algorithm

2021 ◽  
Vol 20 (01) ◽  
pp. 2150013
Author(s):  
Mohammed Abu-Arqoub ◽  
Wael Hadi ◽  
Abdelraouf Ishtaiwi
Keyword(s):  
Decision Making ◽  
Class Imbalance ◽  
The Other ◽  
Associative Classification ◽  
Rule Based ◽  
New Approach ◽  
New Novel ◽  
Accuracy Measure ◽  
High Level ◽  
Substantial Interest

Associative Classification (AC) classifiers are of substantial interest due to their ability to be utilised for mining vast sets of rules. However, researchers over the decades have shown that a large number of these mined rules are trivial, irrelevant, redundant, and sometimes harmful, as they can cause decision-making bias. Accordingly, in our paper, we address these challenges and propose a new novel AC approach based on the RIPPER algorithm, which we refer to as ACRIPPER. Our new approach combines the strength of the RIPPER algorithm with the classical AC method, in order to achieve: (1) a reduction in the number of rules being mined, especially those rules that are largely insignificant; (2) a high level of integration among the confidence and support of the rules on one hand and the class imbalance level in the prediction phase on the other hand. Our experimental results, using 20 different well-known datasets, reveal that the proposed ACRIPPER significantly outperforms the well-known rule-based algorithms RIPPER and J48. Moreover, ACRIPPER significantly outperforms the current AC-based algorithms CBA, CMAR, ECBA, FACA, and ACPRISM. Finally, ACRIPPER is found to achieve the best average and ranking on the accuracy measure.

Transfer Reinforcement Learning for Autonomous Driving

2021 ◽  
Vol 31 (3) ◽  
pp. 1-26
Author(s):  
Aravind Balakrishnan ◽  
Jaeyoung Lee ◽  
Ashish Gaurav ◽  
Krzysztof Czarnecki ◽  
Sean Sedwards
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Transfer Problem ◽  
Autonomous Driving ◽  
High Fidelity ◽  
Rule Based ◽  
High Level ◽  
Real Vehicle

Reinforcement learning (RL) is an attractive way to implement high-level decision-making policies for autonomous driving, but learning directly from a real vehicle or a high-fidelity simulator is variously infeasible. We therefore consider the problem of transfer reinforcement learning and study how a policy learned in a simple environment using WiseMove can be transferred to our high-fidelity simulator, W ise M ove . WiseMove is a framework to study safety and other aspects of RL for autonomous driving. W ise M ove accurately reproduces the dynamics and software stack of our real vehicle. We find that the accurately modelled perception errors in W ise M ove contribute the most to the transfer problem. These errors, when even naively modelled in WiseMove , provide an RL policy that performs better in W ise M ove than a hand-crafted rule-based policy. Applying domain randomization to the environment in WiseMove yields an even better policy. The final RL policy reduces the failures due to perception errors from 10% to 2.75%. We also observe that the RL policy has significantly less reliance on velocity compared to the rule-based policy, having learned that its measurement is unreliable.

Regret in Decision Making

2002 ◽  
Vol 11 (6) ◽  
pp. 212-216 ◽  
Author(s):  
Terry Connolly ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Making ◽  
Comparative Evaluation ◽  
The Other ◽  
Research Issues ◽  
New Approach ◽  
Self Blame ◽  
Psychology And Economics ◽  
Core Components ◽  
Decision Research

Decision research has only recently started to take seriously the role of emotions in choices and decisions. Regret is the emotion that has received the most attention. In this article, we sample a number of the initial regret studies from psychology and economics, and trace some of the complexities and contradictions to which they led. We then sketch a new theory, decision justification theory (DJT), which synthesizes several apparently conflicting findings. DJT postulates two core components of decision–related regret, one associated with the (comparative) evaluation of the outcome, the other with the feeling of self–blame for having made a poor choice. We reinterpret several existing studies in DJT terms. We then report some new studies that directly tested (and support) DJT, and propose a number of research issues that follow from this new approach to regret.

Emotion in the Pursuit of Understanding

2010 ◽  
Vol 1 (2) ◽  
pp. 1-11 ◽  
Author(s):  
Daniel S. Levine ◽  
Leonid I. Perlovsky
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Systems Approach ◽  
Brain Regions ◽  
The Other ◽  
Neural Network Modeling ◽  
Dual Systems ◽  
Affective Component ◽  
Long Time ◽  
High Level

Theories of cognitive processes, such as decision making and creative problem solving, for a long time neglected the contributions of emotion or affect in favor of analysis based on use of deliberative rules to optimize performance. Since the 1990s, emotion has increasingly been incorporated into theories of these cognitive processes. Some theorists have in fact posited a “dual-systems approach” to understanding decision making and high-level cognition. One system is fast, emotional, and intuitive, while the other is slow, rational, and deliberative. However, one’s understanding of the relevant brain regions indicate that emotional and rational processes are deeply intertwined, with each exerting major influences on the functioning of the other. Also presented in this paper are neural network modeling principles that may capture the interrelationships of emotion and cognition. The authors also review evidence that humans, and possibly other mammals, possess a “knowledge instinct,” which acts as a drive to make sense of the environment. This drive typically incorporates a strong affective component in the form of aesthetic fulfillment or dissatisfaction.

scholarly journals A new approach to instruction-idioms detection in a retargetable decompiler

2014 ◽  
Vol 11 (4) ◽  
pp. 1337-1359
Author(s):  
Jakub Křoustek ◽  
Fridolín Pokorný ◽  
Dusan Kolář
Keyword(s):  
The Other ◽  
The Novel ◽  
Previous Approach ◽  
New Approach ◽  
Novel Approach ◽  
Advanced Analysis ◽  
Complex Instruction ◽  
Optimized Code ◽  
High Level ◽  
Later Phase

Retargetable executable-code decompilation is a one of the most complicated reverse-engineering tasks. Among others, it involves de-optimization of compiler-optimized code. One type of such an optimization is usage of so-called instruction idioms. These idioms are used to produce faster or even smaller executable files. On the other hand, decompilation of instruction idioms without any advanced analysis produces almost unreadable high-level language code that may confuse the user of the decompiler. In this paper, we revisit and extend the previous approach of instruction-idioms detection used in a retargetable decompiler developed within the Lissom project. The previous approach was based on detection of instruction idioms in a very-early phase of decompilation (a front-end part) and it was inaccurate for architectures with a complex instruction set (e.g. Intel x86). The novel approach is based on delaying detection of idioms and reconstruction of code to the later phase (a middleend part). For this purpose, we use the LLVM optimizer and we implement this analysis as a new pass in this tool. According to experimental results, this new approach significantly outperforms the previous approach as well as the other commercial solutions.

Nonmanipulable Collective Decision-Making for Games

2012 ◽  
pp. 67-81
Author(s):  
Rob LeGrand ◽  
Timothy Roden ◽  
Ron K. Cytron
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Collective Decision ◽  
The Other ◽  
Collective Decision Making ◽  
Game Development ◽  
New Approach ◽  
Collective Decisions ◽  
Higher Dimensional ◽  
Game Players

This chapter explores a new approach that may be used in game development to help human players and/or non-player characters make collective decisions. The chapter describes how previous work can be applied to allow game players to form a consensus from a simple range of possible outcomes in such a way that no player can manipulate it at the expense of the other players. Then, the text extends that result and shows how nonmanipulable consensus can be found in higher-dimensional outcome spaces. The results may be useful when developing artificial intelligence for non-player characters or constructing frameworks to aid cooperation among human players.

Emotion in the Pursuit of Understanding

2012 ◽  
pp. 106-117 ◽  
Author(s):  
Daniel S. Levine ◽  
Leonid I. Perlovsky
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Systems Approach ◽  
Brain Regions ◽  
The Other ◽  
Neural Network Modeling ◽  
Affective Component ◽  
Long Time ◽  
High Level ◽  
Modeling Principles

Theories of cognitive processes, such as decision making and creative problem solving, for a long time neglected the contributions of emotion or affect in favor of analysis based on use of deliberative rules to optimize performance. Since the 1990s, emotion has increasingly been incorporated into theories of these cognitive processes. Some theorists have in fact posited a “dual-systems approach” to understanding decision making and high-level cognition. One system is fast, emotional, and intuitive, while the other is slow, rational, and deliberative. However, one’s understanding of the relevant brain regions indicate that emotional and rational processes are deeply intertwined, with each exerting major influences on the functioning of the other. Also presented in this paper are neural network modeling principles that may capture the interrelationships of emotion and cognition. The authors also review evidence that humans, and possibly other mammals, possess a “knowledge instinct,” which acts as a drive to make sense of the environment. This drive typically incorporates a strong affective component in the form of aesthetic fulfillment or dissatisfaction.

Being Certain About Uncertainty: How the Representation of System Reliability Affects Pilot Decision Making

1998 ◽  
Vol 42 (1) ◽  
pp. 36-39 ◽  
Author(s):  
Simon Banbury ◽  
Stephen Selcon ◽  
Mica Endsley ◽  
Tessa Gorton ◽  
Kerry Tatlock
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
System Reliability ◽  
Design Guidelines ◽  
The Other ◽  
System Uncertainty ◽  
Secondary Target ◽  
Current Trends ◽  
Primary Identification ◽  
High Level

The present study investigated how pilot decision making is affected by the manner in which the decision support information regarding system reliability is presented, by requiring aircrew participants to respond to a machine-identified target with a “shoot/no shoot” decision. The study investigated whether the provision of an alternate option to the primary identification would affect the decision to shoot, especially if this secondary option was either another enemy aircraft or a friendly fighter. In addition, two different representations were evaluated; one in which the information was presented as system uncertainty; and the other in which it was presented as system confidence. The results indicated that decision making behaviour changed when the system explicitly identified a friendly aircraft as the secondary target — prior willingness to fire on a target with a relatively high level of uncertainty disappeared. The time taken to make the decision was also found to be mediated by what information was given. These results are interpreted in the light of current trends in decision support development and design guidelines are discussed.

scholarly journals Decision making Relation to Emotions management at Headmasters of Secondary and Preparatory Schools

2019 ◽  
pp. 567-592
Author(s):  
Noora Hazim Jawad
Keyword(s):  
Decision Making ◽  
Secondary Schools ◽  
Emotion Management ◽  
The Other ◽  
High Ability ◽  
Emotional Management ◽  
The Third ◽  
Preparatory Schools ◽  
High Level ◽  
The Relationship

The research aimed to measure decision-making, measure emotion management, know the nature of the relationship between decision-making and emotion management of the principals of middle and Secondary Schools. To achieve the objectives of the research, two tools were used, namely the decision-making scale and the emotional management scale adopted by the researcher. The other measure of emotion management consists of (42) paragraphs, the current research sample consisted of (111) managers and managers of the third Karkh education. The results showed that managers have a high level of decision-making ability, that managers have a high ability to manage emotions.

scholarly journals The Market as a Decision-Making Mechanism in a Democracy

2015 ◽  
Vol 7 (11) ◽  
pp. 260
Author(s):  
Panagiotis Evangelopoulos
Keyword(s):  
Decision Making ◽  
Majority Rule ◽  
The Other ◽  
Modern Democracy ◽  
Effective Protection ◽  
Effective Decision ◽  
Effective Decision Making ◽  
The Individual ◽  
High Level ◽  
Voting Mechanism

In my paper I attempt to show that the market is an effective decision-making mechanism in a modern democracy. On the other hand, in a contemporary democratic society, the state must have a limited role, only on the formation of the collective choice through the majority rule. The majority rule is required for the proper functioning of social organization, with the voting mechanism within a framework of strict limitations imposed by individuals with high-level constitutional backing for the effective protection of the individual rights.

scholarly journals Sensory criteria assessment of fruit from Averrhoa bilimbi L. with comparison of Eckenrode and Fuzzy Eckenrode method

2021 ◽  
Vol 922 (1) ◽  
pp. 012007
Author(s):  
R Agustina ◽  
S Hartuti
Keyword(s):  
Decision Making ◽  
Natural Product ◽  
The Other ◽  
Sensory Assessment ◽  
Simple Method ◽  
Fuzzy Method ◽  
Other Hand ◽  
Decision Making System ◽  
Processed Products ◽  
High Level

Abstract The fruit candy made of processed products made from the natural fruit of Averhoa bilimbi L. whose production was abundant, recently a few to utilization. The main objective of this study was to examine the assessment of sensory criteria fruit candy from A. bilimbi with comparison of eckenrode and fuzzy eckenrode method. The results showed fruit candy contains a higher value of colour (0.239), wherein the aroma (0.169), taste (0.183), texture (0.211), and the overall acceptance (0.197) using the eckenrode method. On the other hand, based on the fuzzy eckenrode method were shown the value of colour (0.224), taste (0.187), aroma (183), texture (0.2110 and overall acceptance (0.195). Although the comparison from eckenrode and fuzzy eckenrode method appear quite stable for criterias of sensory. Finding the optimum value for an aroma in the perception of colour from fruit candy higher to eckenrode than fuzzy method. The eckenrode method provided a dynamic space in a high-level decision-making system to differ significantly. Therefore, the eckenrode method was a quite simple method to establish decisions for weighting a more definite critera in decision making in sensory assessment to develop a natural product from A. bilimbi.

Sign in / Sign up

Export Citation Format

Share Document