The study of what actions an agent should take in a stochastic environment in order to maximize a cumulative reward.

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42 views

How do humans learn to combine tasks?

I've been reading about hierarchical learning (a variant of reinforcement learning from what I understand) and how it is shown to allow learning of a higher-level task (the main example is assembly). ...
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0answers
22 views

Frequency estimation in binary prediction task

In a binary prediction task, people often match choice probabilities to outcome probabilities (a phenomenon known as probability matching). However, under certain circumstances (eg, existence of a ...
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0answers
17 views

Structure for General Intelligence

I've just read Dan Rasmussen's paper on general intelligence and I was wondering what other approaches for complex, scalable and adaptable learning have been tried in the past? This question's scope ...
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1answer
38 views

What evidence is there to suggest that delayed gratification is taught and learned and not genetic?

Every evening I spend considerable time and energy trying to get my kids to eat their dinner, holding off treats such as chips or dessert. My experience was that my parents did the same. I have ...
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0answers
26 views

A basic question on reinforcement learning

Reinforcement learning is defined not by characterizing learning methods, but by characterizing a learning problem. Any method that is well suited to solving that problem, we consider to be a ...
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1answer
156 views

What causes behavioural inhibition?

There are obvious consequences that prevent people from behaving anti-socially or criminally. However there are many behaviours that are within the bounds of social norms, yet there seems to be some ...
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1answer
52 views

Is it possible to create an inhibition against some activities?

There is an unexplained psychological reason that causes one not to be able to do some random activities (for instance, not being able to eat several days because one's mouth just won't open to take ...
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0answers
181 views

'Model-free' learning in humans

In reinforcement learning, there is a stark distinction between model-based and model-free learning algorithms, where model-free methods don't make use any explicit information about the dynamics of ...
10
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1answer
217 views

Are there any connectionist models that integrate reinforcement and fully supervised learning?

I've been working on modeling some phenomena involving real-time control in an environment with inherent rewards (specifically, playing a 'pong'-like game), and it's increasingly looking like ...
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0answers
523 views

How does goal-tracking and sign-tracking behaviour vary across species?

In Pavlonian (Classical) Conditioning, conditioned responses of an animal may vary. Some animals focus on the unconditioned stimulus (ie. food / location of food) while others may focus on the ...
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0answers
240 views

Refinements of Rescorla-Wagner model of classical conditioning

The Rescorla-Wagner model is one of the most commonly discussed mathematical models of classical conditioning. It was wildly popular when it came out in 1972, and very successful. The same math, is ...