Key: objective mismatch problem, capture causal representation for both states and actions ExpEnv: list, unlock, crash Model-Based Transfer Learning for Contextual Reinforcement Learning Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu Key: bayesian optimization, contextual rl ExpEnv: gaussian ...
Bayesian Model Averaging Component Feature Engineering: We apply feature engineering techniques to capture more information about the data. For this, we implement polynomial features to increase the complexity of the feature space. Ensemble Methods: We have implemented an ensemble method called “Weighted...
Constrained multi-objective optimization assisted by convergence and diversity auxiliary tasks Engineering Applications of Artificial Intelligence, Volume 139, Part A, 2025, Article 109546 Qianlong Dang,…, Shuai Yang Adversarial-Causal Representation Learning Networks for Machine fault diagnosis under unseen ...
This study examined the correspondence between individual differences in model-based/model-free dependence and individual difference in social preferences, and thus no defini- tive claims can be made regarding the causal relationship between the two. Another factor that may influence individual differences...
Step 2. Complete the performance-based optimization decomposition using the theory in Section 2.1 to obtain subsystems. Step 3. Construct causal graphical models of the subsystems using the scheme in Section 2.2. Step 4. Design the statistical information for the monitoring subsystem is Equation (...
The dynamic Bayesian networks (DBNs) are applied in degradation process to solve the uncertainty problem. BNs or DBNs is widely used because of their ability of cope with uncertainties present in decision-making, which provides a method for representing causal information (Adedipe, Shafiee, & Zio,...
13 emphasized the importance of consumer-perceived control to service failure, and compared the perceived control time model with the causal attribution model to analyze consumers’ emotional and behavioral responses after a service failure. The results demonstrated that the temporal model of perceptual ...
Schwarzer R, Jerusalem M, Weinman J, Wright S, Johnston M. Measures in health psychology: A user’s portfolio. Causal and control beliefs. Causal Control Beliefs. 1995;1(011):35–7. Google Scholar Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the...
Given the prior information, the probability of subsequent events in a causal structure can be dynamically updated by Bayesian theory using observed data. Bayesian theory was used in various fields, e.g., system lifetime estimation and risk analysis (Guo et al., 2019; Wang et al., 2020; Zh...
Based on the causal relationship among the index factors in the evaluation index scheme of institution pupils’ entrepreneurial risk, the Bayesian network topology is constructed, the conditional probability of node variables in the topology is determined by triangular fuzzy numbers, and the college stud...