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Interval division and linearization algorithm for minimax linear fractional program
This paper constructs an interval partition linearization algorithm for solving minimax linear fractional programming (MLFP) problem. In this...
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Minimax Methods
In many scientific and engineering applications it is often necessary to minimize the maximum of some quantity with respect to one or more...
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Heuristics: 2-Person Games and Theoretical Constraints
► Chapter 5 introduced a methodology for “intelligent” or “heuristic” search. To this point we have used...
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A prompt-based approach to adversarial example generation and robustness enhancement
Recent years have seen the wide application of natural language processing (NLP) models in crucial areas such as finance, medical treatment, and news...
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Sequences
Computers are really good at dealing with large amounts of information. They can repeat a task over and over again without getting bored. When they...
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Miscellaneous Topics
In practice, reinforcement learning is comparatively more challenging for a beginner to use than supervised learning algorithms. The challenges of...
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Fairness for Robust Learning to Rank
While conventional ranking systems focus solely on maximizing the utility of the ranked items to users, fairness-aware ranking systems additionally...
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Scratch-Rec: a novel Scratch recommendation approach adapting user preference and programming skill for enhancing learning to program
Among teenagers, online programming learning platforms, such as Scratch, have obtained promising achievements for guiding beginners. However, with...
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Assessing Policy, Loss and Planning Combinations in Reinforcement Learning Using a New Modular Architecture
The model-based reinforcement learning paradigm, which uses planning algorithms and neural network models, has recently achieved unprecedented...
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Heuristic Search
This text has focused on the interaction of algorithms with data structures. Many of the algorithms presented in this text deal with search and how...
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Unveiling Computer Chess Evolution: Can Machine Learning Detect Historical Trends?
Computer Chess and AI are deeply intertwined, addressing similar research issues and proposing solutions that intersect. Even from a historical...
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Solving NoGo on Small Rectangular Boards
The game of NoGo is similar to Go in terms of rules, but requires very different strategies. While strong heuristic computer players have been...
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Gobang Game Algorithm Based on Reinforcement Learning
The traditional Gobang game program generally evaluates the chess type, and the game power mostly depends on the developer’s understanding of Gobang....
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Search, Games and Problem Solving
The search for a solution in an extremely large search tree presents a problem for nearly all inference systems. From the starting state there are...
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Sets and Maps
In the last chapter we studied sequences which are used to keep track of lists of things where duplicate values are allowed. For instance, there can...
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Incremental Elicitation of Preferences: Optimist or Pessimist?
In robust incremental elicitation, it is quite common to make recommendations and to select queries by using a minimax regret criterion, which...
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SOCP approach to robust twin parametric margin support vector machine
Twin parametric-margin support vector machine (TPMSVM) is one of the classification tools based on parametric margin ν -SVM (par- ν -SVM) and twin SVM...
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