Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning, communication, and memory become increasingly important. Hover, successfully evolving such cognitive abilities remains difficult.  argues that a main cause for such difficulty is deception, i.e. evolution converges to a behavior unrelated to the desired solution. More specifically, cognitive behaviors often require accumulating neural structure that provides no immediate fitness benefit, and evolution often thus converges to non-cognitive solutions. To investigate this hypothesis, a common evolutionary robotics T-Maze domain is adapted in three separate ways to require agents to communicate, remember, and learn. Indicative of deception, evolution driven by objective-based fitness often converges upon simple non-cognitive behaviors. In contrast, evolution driven to explore novel behaviors, i.e. novelty search, often evolves the desired cognitive behaviors. The conclusion is that open-ended methods of evolution may better recognize and reward the stepping stones that are necessary for cognitive behavior to emerge.
['Joel Lehman', 'Risto Miikkulainen']
I am writing a research paper on a idea Overcoming deception in evolution of cognitive behaviors
[{"from": "human", "value": "I am writing a research paper on a idea Overcoming deception in evolution of cognitive behaviors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning, communication, and memory become increasingly important. Hover, successfully evolving such cognitive abilities remains difficult.  argues that a main cause for such difficulty is deception, i.e. evolution converges to a behavior unrelated to the desired solution. More specifically, cognitive behaviors often require accumulating neural structure that provides no immediate fitness benefit, and evolution often thus converges to non-cognitive solutions. To investigate this hypothesis, a common evolutionary robotics T-Maze domain is adapted in three separate ways to require agents to communicate, remember, and learn. Indicative of deception, evolution driven by objective-based fitness often converges upon simple non-cognitive behaviors. In contrast, evolution driven to explore novel behaviors, i.e. novelty search, often evolves the desired cognitive behaviors. The conclusion is that open-ended methods of evolution may better recognize and reward the stepping stones that are necessary for cognitive behavior to emerge."}]