Agent learning of FilmTrust dataset across various parameters. by Muhammad Waqar (500788)

Single agent and multi-agents tasks for <i>LazyAct</i>. by Hongjie Zhang (136127)

“…Specifically, each decision made by an agent requires a complete neural network computation, leading to a linear increase in computational cost with the number of interactions and agents. …”

The agent-environment interaction in reinforcement learning [3]. by Raed Alharthi (18340157)

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Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

Agent learning of ML100K dataset across various parameters. by Muhammad Waqar (500788)

Agent learning of ML latest-small dataset across various parameters. by Muhammad Waqar (500788)

SIPPO Algorithm for Continuous-Space Facility Location by Mack Jie (21536510)

Network architectures for multi-agents task. by Hongjie Zhang (136127)

“…Specifically, each decision made by an agent requires a complete neural network computation, leading to a linear increase in computational cost with the number of interactions and agents. …”

Results of using the algorithm to find the chemical constituents for compounds using dual energy and mass attenuation coefficient. by Dong Hyeok Choi (12562048)

Results of using the algorithm to find the chemical constituents for mixtures using dual energy and mass attenuation coefficient. by Dong Hyeok Choi (12562048)

Time(s) and GFLOPs savings of single-agent tasks. by Hongjie Zhang (136127)

“…Specifically, each decision made by an agent requires a complete neural network computation, leading to a linear increase in computational cost with the number of interactions and agents. …”

Hyperparameters for all agents. by Hasan Raza Khanzada (22404835)

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Comparison of RL agents. by Hasan Raza Khanzada (22404835)

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A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

Scores vs Skip ratios on single-agent task. by Hongjie Zhang (136127)

“…Specifically, each decision made by an agent requires a complete neural network computation, leading to a linear increase in computational cost with the number of interactions and agents. …”

Data and code resources. by Sam Hall-McMaster (10343795)

Comparison of PID and RL agents. by Hasan Raza Khanzada (22404835)

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Evaluation criteria for RL agents. by Hasan Raza Khanzada (22404835)

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Training process for RL agents. by Hasan Raza Khanzada (22404835)

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Win rate vs Skip ratios on multi-agents tasks. by Hongjie Zhang (136127)

“…Specifically, each decision made by an agent requires a complete neural network computation, leading to a linear increase in computational cost with the number of interactions and agents. …”