Emotion AI Leap
Our team's Emotion Simulation System (ESYS) at Toronto Metropolitan University is at the vanguard of endowing robots with the situational responsiveness akin to human emotions. This advancement bridges the gap between cold computation and the warm complexity of human feeling, setting the stage for a new breed of intelligent machines.
Emotion AI Leap
Our team's Emotion Simulation System (ESYS) at Toronto Metropolitan University is at the vanguard of endowing robots with the situational responsiveness akin to human emotions. This advancement bridges the gap between cold computation and the warm complexity of human feeling, setting the stage for a new breed of intelligent machines.
Emotion AI Leap
Our team's Emotion Simulation System (ESYS) at Toronto Metropolitan University is at the vanguard of endowing robots with the situational responsiveness akin to human emotions. This advancement bridges the gap between cold computation and the warm complexity of human feeling, setting the stage for a new breed of intelligent machines.
Project
PhD Research
Role
Researcher & Engineer
Year
2024 - 2026
Evolutionary Robotics
Our journey begins with a fundamental question: Why do we, as humans, feel emotions? Evolutionary biologists suggest that emotions evolved as essential tools for survival, allowing us to navigate and react to the world around us swiftly. By looking to the evolutionary roots of human behavior, we're innovating ways for robots to not just 'do' but also 'feel' in their interactions.
Evolutionary Robotics
Our journey begins with a fundamental question: Why do we, as humans, feel emotions? Evolutionary biologists suggest that emotions evolved as essential tools for survival, allowing us to navigate and react to the world around us swiftly. By looking to the evolutionary roots of human behavior, we're innovating ways for robots to not just 'do' but also 'feel' in their interactions.
AI's Unpredictability Quandary
In facing unpredictable challenges, AI robots often require human intervention. Our response? The integration of emotional intelligence through ESYS.
AI's Unpredictability Quandary
In facing unpredictable challenges, AI robots often require human intervention. Our response? The integration of emotional intelligence through ESYS.
AI's Unpredictability Quandary
In facing unpredictable challenges, AI robots often require human intervention. Our response? The integration of emotional intelligence through ESYS.
Introducing ESYS
We're infusing robots with a cognitive and emotional framework inspired by the human response system, coding for more than just task completion—coding for survival.
Introducing ESYS
We're infusing robots with a cognitive and emotional framework inspired by the human response system, coding for more than just task completion—coding for survival.
Introducing ESYS
We're infusing robots with a cognitive and emotional framework inspired by the human response system, coding for more than just task completion—coding for survival.
Detailed Experiment Setup
Maze Navigation: Our Python-crafted maze is a testbed for autonomous navigation, featuring orange and red tiles that signal different hazards.
Dual Pac-Man Agents: We programmed two sets of 'Pac-Man' agents: one endowed with ESYS to process these colors as emotional triggers and the other following conventional A* pathfinding without emotional context.
Adaptive vs. Algorithmic: Across 100 maze runs, the ESYS 'Pac-Men' faced off against standard 'Pac-Men' in a direct comparison of navigation under pressure.
Assessing the AI: We evaluated their success by the damage avoided and the efficiency of exit discovery, spotlighting the impact of emotional intelligence on performance.
Detailed Experiment Setup
Maze Navigation: Our Python-crafted maze is a testbed for autonomous navigation, featuring orange and red tiles that signal different hazards.
Dual Pac-Man Agents: We programmed two sets of 'Pac-Man' agents: one endowed with ESYS to process these colors as emotional triggers and the other following conventional A* pathfinding without emotional context.
Adaptive vs. Algorithmic: Across 100 maze runs, the ESYS 'Pac-Men' faced off against standard 'Pac-Men' in a direct comparison of navigation under pressure.
Assessing the AI: We evaluated their success by the damage avoided and the efficiency of exit discovery, spotlighting the impact of emotional intelligence on performance.
Detailed Experiment Setup
Maze Navigation: Our Python-crafted maze is a testbed for autonomous navigation, featuring orange and red tiles that signal different hazards.
Dual Pac-Man Agents: We programmed two sets of 'Pac-Man' agents: one endowed with ESYS to process these colors as emotional triggers and the other following conventional A* pathfinding without emotional context.
Adaptive vs. Algorithmic: Across 100 maze runs, the ESYS 'Pac-Men' faced off against standard 'Pac-Men' in a direct comparison of navigation under pressure.
Assessing the AI: We evaluated their success by the damage avoided and the efficiency of exit discovery, spotlighting the impact of emotional intelligence on performance.
The Findings
The ESYS-enabled 'Pac-Men' outperformed their traditional counterparts, negotiating the maze with zero collateral damage and displaying a near-human capacity for strategic adaptation.
The Insights Revealed
Enhanced Safety: ESYS 'Pac-Men' showed superior hazard navigation, avoiding damages entirely.
Strategic Depth: Their decision-making mirrored the nuanced problem-solving skills of humans, proving the model's advanced cognitive abilities.
Reduced Dependence: The need for human intervention dropped substantially, showcasing the ESYS robots' improved self-reliance.
The Findings
The ESYS-enabled 'Pac-Men' outperformed their traditional counterparts, negotiating the maze with zero collateral damage and displaying a near-human capacity for strategic adaptation.
The Insights Revealed
Enhanced Safety: ESYS 'Pac-Men' showed superior hazard navigation, avoiding damages entirely.
Strategic Depth: Their decision-making mirrored the nuanced problem-solving skills of humans, proving the model's advanced cognitive abilities.
Reduced Dependence: The need for human intervention dropped substantially, showcasing the ESYS robots' improved self-reliance.
The Findings
The ESYS-enabled 'Pac-Men' outperformed their traditional counterparts, negotiating the maze with zero collateral damage and displaying a near-human capacity for strategic adaptation.
The Insights Revealed
Enhanced Safety: ESYS 'Pac-Men' showed superior hazard navigation, avoiding damages entirely.
Strategic Depth: Their decision-making mirrored the nuanced problem-solving skills of humans, proving the model's advanced cognitive abilities.
Reduced Dependence: The need for human intervention dropped substantially, showcasing the ESYS robots' improved self-reliance.
The Future is Feeling
With these breakthroughs, we're now preparing to take ESYS from controlled environments to real-world applications. This technology promises to enhance the operational capacity of robots in sectors from disaster recovery to space exploration.
The Future is Feeling
With these breakthroughs, we're now preparing to take ESYS from controlled environments to real-world applications. This technology promises to enhance the operational capacity of robots in sectors from disaster recovery to space exploration.
The Future is Feeling
With these breakthroughs, we're now preparing to take ESYS from controlled environments to real-world applications. This technology promises to enhance the operational capacity of robots in sectors from disaster recovery to space exploration.
Outcome
Our research, detailed in an IEEE paper, confirms the ESYS model's effectiveness: robots navigated with zero damage, their speed was consistent with traditional methods, and human intervention was significantly reduced. These findings underscore the ESYS model's potential in real-world applications, where it can now be extended for field testing in robot applications, offering a new standard for autonomous robotic systems.
Outcome
Our research, detailed in an IEEE paper, confirms the ESYS model's effectiveness: robots navigated with zero damage, their speed was consistent with traditional methods, and human intervention was significantly reduced. These findings underscore the ESYS model's potential in real-world applications, where it can now be extended for field testing in robot applications, offering a new standard for autonomous robotic systems.
Outcome
Our research, detailed in an IEEE paper, confirms the ESYS model's effectiveness: robots navigated with zero damage, their speed was consistent with traditional methods, and human intervention was significantly reduced. These findings underscore the ESYS model's potential in real-world applications, where it can now be extended for field testing in robot applications, offering a new standard for autonomous robotic systems.
Made by
Good
Humans.
Evolutionary Robotics
Our journey begins with a fundamental question: Why do we, as humans, feel emotions? Evolutionary biologists suggest that emotions evolved as essential tools for survival, allowing us to navigate and react to the world around us swiftly. By looking to the evolutionary roots of human behavior, we're innovating ways for robots to not just 'do' but also 'feel' in their interactions.
Evolutionary Robotics
Our journey begins with a fundamental question: Why do we, as humans, feel emotions? Evolutionary biologists suggest that emotions evolved as essential tools for survival, allowing us to navigate and react to the world around us swiftly. By looking to the evolutionary roots of human behavior, we're innovating ways for robots to not just 'do' but also 'feel' in their interactions.