Majid Nili Ahmadabadi
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View article: Better than Maximum Likelihood Estimation of Model-based and Model-free Learning Styles
Better than Maximum Likelihood Estimation of Model-based and Model-free Learning Styles Open
View article: Deformed Probability Estimation in Goal-Directed reinforcement learning model explains anxious-depression dimensions of psychiatric disorders
Deformed Probability Estimation in Goal-Directed reinforcement learning model explains anxious-depression dimensions of psychiatric disorders Open
Psychiatric disorders are complex, multi-dimensional pathologies rooted in diverse cognitive processes. Computational psychiatry aims to reveal distortions in these processes through behavior modeling, providing a deeper understanding of p…
View article: DEEPQUESTION: Systematic Generation of Real-World Challenges for Evaluating LLMs Performance
DEEPQUESTION: Systematic Generation of Real-World Challenges for Evaluating LLMs Performance Open
LLMs often excel on standard benchmarks but falter on real-world tasks. We introduce DeepQuestion, a scalable automated framework that augments existing datasets based on Bloom's taxonomy and creates novel questions that trace original sol…
View article: Three Benefits of Using Nonlinear Compliance in Robotic Systems Performing Cyclic Tasks: Energy Efficiency, Control Robustness, and Gait Optimality
Three Benefits of Using Nonlinear Compliance in Robotic Systems Performing Cyclic Tasks: Energy Efficiency, Control Robustness, and Gait Optimality Open
Nonlinearity in parallel compliance can be exploited to improve the performance of locomotion systems in terms of (1) energy efficiency, (2) control robustness, and (3) gait optimality; that is, attaining energy efficiency across a set of …
View article: Decision-Making in Sharing Personal Information of Others: An Empirical Investigation
Decision-Making in Sharing Personal Information of Others: An Empirical Investigation Open
The sharing of personal information by data collection entities has significantly impacted social processes, especially in recent years. This study aimed to examine the relationship between dark personality traits (Machiavellianism, psycho…
View article: Subgoal Discovery Using a Free Energy Paradigm and State Aggregations
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations Open
Reinforcement learning (RL) plays a major role in solving complex sequential decision-making tasks. Hierarchical and goal-conditioned RL are promising methods for dealing with two major problems in RL, namely sample inefficiency and diffic…
View article: Optimizing Alignment with Less: Leveraging Data Augmentation for Personalized Evaluation
Optimizing Alignment with Less: Leveraging Data Augmentation for Personalized Evaluation Open
Automatic evaluation by large language models (LLMs) is a prominent topic today; however, judgment and evaluation tasks are often subjective and influenced by various factors, making adaptation challenging. While many studies demonstrate t…
View article: AI-powered Digital Framework for Personalized Economical Quality Learning at Scale
AI-powered Digital Framework for Personalized Economical Quality Learning at Scale Open
The disparity in access to quality education is significant, both between developed and developing countries and within nations, regardless of their economic status. Socioeconomic barriers and rapid changes in the job market further intens…
View article: A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback
A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback Open
Reinforcement learning (RL) is one of the active fields in machine learning, demonstrating remarkable potential in tackling real-world challenges. Despite its promising prospects, this methodology has encountered with issues and challenges…
View article: CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt
CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt Open
Text classification is a fundamental task in natural language processing (NLP), and large language models (LLMs) have demonstrated their capability to perform this task across various domains. However, the performance of LLMs heavily depen…
View article: Risk Sensitivity in Markov Games and Multi-Agent Reinforcement Learning: A Systematic Review
Risk Sensitivity in Markov Games and Multi-Agent Reinforcement Learning: A Systematic Review Open
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been risk-neutral, i.e., agents are assumed to optimize a perform…
View article: Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach Open
Personalized AI-based services involve a population of individual reinforcement learning agents. However, most reinforcement learning algorithms focus on harnessing individual learning and fail to leverage the social learning capabilities …
View article: The effects of directed and free self-monitoring on goal-directed and habitual decision-making
The effects of directed and free self-monitoring on goal-directed and habitual decision-making Open
Many studies on humans and animals have provided evidence for the contribution of goal-directed and habitual valuation systems in learning and decision-making. However, how the arbitration between these two systems is affected by other cog…
View article: Better Than Maximum Likelihood Estimation of Model- based and Model-free Learning Styles
Better Than Maximum Likelihood Estimation of Model- based and Model-free Learning Styles Open
Various decision-making systems work together to shape human behavior. Goal-directed and habitual systems are the two most important systems studied by reinforcement learning (RL) through model-based (MB) and model-free (MF) learning style…
View article: Uncovering hidden network architecture from spiking activities using an exact statistical input-output relation of neurons
Uncovering hidden network architecture from spiking activities using an exact statistical input-output relation of neurons Open
View article: Learning from Different Perspectives for Regret Reduction in Reinforcement Learning: A Free Energy Approach
Learning from Different Perspectives for Regret Reduction in Reinforcement Learning: A Free Energy Approach Open
View article: Improving Muscle Force Distribution Model Using Reflex Excitation: Toward a Model-Based Exoskeleton Torque Optimization Approach
Improving Muscle Force Distribution Model Using Reflex Excitation: Toward a Model-Based Exoskeleton Torque Optimization Approach Open
74% of biological torque at the ankle joint cannot be experimentally compensated and the existing models can only explain that 17% of the biological torque is uncompensable. Our improved model can explain that 58% of biological torque is u…
View article: Do you share your personally useless information if others may benefit from it?
Do you share your personally useless information if others may benefit from it? Open
Information is personally useless if its beholder cannot individually benefit from it further unless she shares it with those who can exploit that information to increase their mutual outcome. We study sharing such information anonymously …
View article: Design and validation of augmented reality content production model with emphasis on constructivism approach
Design and validation of augmented reality content production model with emphasis on constructivism approach Open
Background and Objectives: Due to the growing need of learners for new digital technologies in education, especially augmented reality technology, which has significant potential, the inadequacy of common electronic content, their lack of …
View article: Effects of Reduced Achilles Subtendons Relative Displacement on Healthy Elderly Walking: A Simulation Study
Effects of Reduced Achilles Subtendons Relative Displacement on Healthy Elderly Walking: A Simulation Study Open
Walking in healthy elderly people is characterized by lower performance. Since conventional training programs have had limited success in improving gait performance, it is essential to identify underlying causes of walking deficits in heal…
View article: Implicit Counterfactual Effect in Partial Feedback Reinforcement Learning: Behavioral and Modeling Approach
Implicit Counterfactual Effect in Partial Feedback Reinforcement Learning: Behavioral and Modeling Approach Open
Context remarkably affects learning behavior by adjusting option values according to the distribution of available options. Displaying counterfactual outcomes, the outcomes of the unchosen option alongside the chosen one (i.e., providing c…
View article: Effects of methylphenidate on reinforcement learning depend on working memory capacity
Effects of methylphenidate on reinforcement learning depend on working memory capacity Open
View article: Better Than Maximum Likelihood Estimation of Model-Based And Model-Free Learning Style
Better Than Maximum Likelihood Estimation of Model-Based And Model-Free Learning Style Open
Various decision-making systems work together to shape human behavior. Habitual and goal-directed systems are the two most important ones that are studied by reinforcement learning (RL), using model-free and model-based learning methods, r…
View article: Simulation-based biomechanical assessment of unpowered exoskeletons for running
Simulation-based biomechanical assessment of unpowered exoskeletons for running Open
View article: Optimal Reinforcement Learning with Asymmetric Updating in Volatile Environments: a Simulation Study
Optimal Reinforcement Learning with Asymmetric Updating in Volatile Environments: a Simulation Study Open
A bstract The ability to predict the future is essential for decision-making and interaction with the environment to avoid punishment and gain reward. Reinforcement learning algorithms provide a normative way for interactive learning, espe…
View article: Reinforcement Learning with Subspaces using Free Energy Paradigm
Reinforcement Learning with Subspaces using Free Energy Paradigm Open
In large-scale problems, standard reinforcement learning algorithms suffer from slow learning speed. In this paper, we follow the framework of using subspaces to tackle this problem. We propose a free-energy minimization framework for sele…
View article: Human-in-the-Loop Weight Compensation in Upper Limb Wearable Robots Towards Total Muscles’ Effort Minimization
Human-in-the-Loop Weight Compensation in Upper Limb Wearable Robots Towards Total Muscles’ Effort Minimization Open
In this paper: (1) We present a novel human-in-the-loop adaptation method for whole arm muscles’ effort minimization by means of weight compensation in the face of an object with an unknown mass. (2) This adaptation rule can also be used a…
View article: Implicit counterfactual effect in partial feedback reinforcement learning: behavioral and modeling approach
Implicit counterfactual effect in partial feedback reinforcement learning: behavioral and modeling approach Open
Context by distorting values of options with respect to the distribution of available alternatives, remarkably affects learning behavior. Providing an explicit counterfactual component, outcome of unchosen option alongside with the chosen …
View article: A Kinematic Index for Estimation of Metabolic Rate Reduction in Running with<i>I-RUN</i>
A Kinematic Index for Estimation of Metabolic Rate Reduction in Running with<i>I-RUN</i> Open
In this paper, we target multiple goals related to our passive running assistive device, called I-RUN . The major goals are: (1) finding the main reason behind individual differences in benefiting from our assistive device at the muscles l…
View article: Using the DEMOTEL-ANP-HSEE Model to evaluate medical units Case study: Case Study: ArabNia Hospital in Qom
Using the DEMOTEL-ANP-HSEE Model to evaluate medical units Case study: Case Study: ArabNia Hospital in Qom Open
Background and aims: Observance of Health, Safety and Environment (HSE) guidelines is becoming more pervasive in all organizations, and governments and regulators are becoming more strict on it. The onset and prevalence of Coronavirus dise…