<p>Reward systems are one of the most actively studied topics in (cognitive) neuroscience and prediction error - that is, deviations from expected "future" reward - play a big role in that. Since you're particularly interested in models, I recommend checking out the work of <a href="http://www.princeton.edu/~matthewb/">Matt Botvinick</a> and <a href="http://www.cns.nyu.edu/~daw/">Nathaniel Daw</a>. Here are a few papers that might be good starting points:</p>

<p>Glascher, Daw, Dayan, &amp; O’Doherty (2010). <a href="http://www.cns.nyu.edu/~daw/gddo10.pdf">States versus Rewards: Dissociable Neural
Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning</a>. <em>Neuron, 66</em>, 585-595.</p>

<p>den Ouden, Friston, Daw, McIntosh, &amp; Stephan (2009). <a href="http://www.cns.nyu.edu/~daw/dfdms08.pdf">A Dual Role for Prediction Error in
Associative Learning</a>. <em>Cerebral Cortex, 19</em>, 1175-1185.</p>

<p>Solway &amp; Botvinick (2012). <a href="http://www.princeton.edu/~matthewb/Publications/SolwayBotvinick_PsychRev_12.pdf">Goal-directed decision making as probabilistic inference: A computational framework and potential neural correlates</a>. <em>Psycholological Review, 119</em>, 120-154.</p>

<p>Botvinick &amp; Plaut (2004). <a href="http://www.cnbc.cmu.edu/~plaut/papers/pdf/BotvinickPlaut04PR.seq-action.pdf">Doing without schema hierarchies: A recurrent connectionist approach to routine sequential action and its pathologies</a>. <em>Psychological Review, 111</em>, 395-429.</p>

CC BY-SA 3.0
2013-01-04T17:55:58.073Z
2013-01-04T17:55:58.073Z
Dan M.
<p>I'm interested in planning and how one is able to take action and plan ahead at the same time. I could imagine one could make observations and project these into the future using past experiences. The reward system could then sort out favorable outcomes which one could aim for, taking the necessary steps.</p>

<p>However I don't know if this is really how the reward system works (I wasn't able to find resources especially for "future" reward) and I can also see difficulties in terms of interference with control of the current situation - planning would have to be handled as some sort of suppressed action.</p>

<p>So are there already cognitive models that try to explain planning and how planning and action could work in parallel (although interacting)?</p>

<cognitive-modeling><motivation><motor><goals>
Are there already models for planning and goal-directed behaviour?
Fabian Fritz
# Are there already models for planning and goal-directed behaviour?

(Asked by: username_0 on 2013-01-04)

I'm interested in planning and how one is able to take action and plan ahead at the same time. I could imagine one could make observations and project these into the future using past experiences. The reward system could then sort out favorable outcomes which one could aim for, taking the necessary steps.

However I don't know if this is really how the reward system works (I wasn't able to find resources especially for "future" reward) and I can also see difficulties in terms of interference with control of the current situation - planning would have to be handled as some sort of suppressed action.

So are there already cognitive models that try to explain planning and how planning and action could work in parallel (although interacting)?

**Tags:** cognitive-modeling, motivation, motor, goals


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## 1 answers

### Answer by username_1 on 2013-01-04. Score: 5 | Accepted answer

Reward systems are one of the most actively studied topics in (cognitive) neuroscience and prediction error - that is, deviations from expected "future" reward - play a big role in that. Since you're particularly interested in models, I recommend checking out the work of [Matt Botvinick](http://www.princeton.edu/~matthewb/) and [Nathaniel Daw](http://www.cns.nyu.edu/~daw/). Here are a few papers that might be good starting points:

Glascher, Daw, Dayan, & O’Doherty (2010). [States versus Rewards: Dissociable Neural
Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning](http://www.cns.nyu.edu/~daw/gddo10.pdf). *Neuron, 66*, 585-595.

den Ouden, Friston, Daw, McIntosh, & Stephan (2009). [A Dual Role for Prediction Error in
Associative Learning](http://www.cns.nyu.edu/~daw/dfdms08.pdf). *Cerebral Cortex, 19*, 1175-1185.

Solway & Botvinick (2012). [Goal-directed decision making as probabilistic inference: A computational framework and potential neural correlates](http://www.princeton.edu/~matthewb/Publications/SolwayBotvinick_PsychRev_12.pdf). *Psycholological Review, 119*, 120-154.

Botvinick & Plaut (2004). [Doing without schema hierarchies: A recurrent connectionist approach to routine sequential action and its pathologies](http://www.cnbc.cmu.edu/~plaut/papers/pdf/BotvinickPlaut04PR.seq-action.pdf). *Psychological Review, 111*, 395-429.


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