Comparative results of each algorithm in comparative experiment. by Junhao Wei (6816803)

“…<p>Comparative results of each algorithm in comparative experiment.</p>…”

The scenario used in Unity environment. Both the agent and target are spawned randomly at the start of the game anywhere in the game environment for each episode. by Enoch Solomon (21416703)

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

Proposed reinforcement learning architecture. by Enoch Solomon (21416703)

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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)

Data supporting figures and tables in Reimagining Electrical Diagrams in Construction: Automated Symbol Detection and Wiring Design and Generation with Deep Learning by IKENNA EKEKE (20996041)

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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. …”

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)

Subjects:

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

Path length variation diagram of each algorithm. by Yun Qi (560401)

Simulation results of each algorithm path map. by Yun Qi (560401)

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)