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geopro:pedro:evolucao [2009/07/14 14:36] pedrogeopro:pedro:evolucao [2009/07/14 15:45] (atual) pedro
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 =====EPIA/SSM 2009===== =====EPIA/SSM 2009=====
-Reviewer 1+==== Reviewer 1 ====
  
-|Summary of paper |This paper studies the conditions where a population of agents reaches equilibrium in evolutionary game theory. + 
-An agent-based model is presented, where individuals compete for space using mixed strategies. The simulation of this model shows that the population’s mean strategy always converges to a stable state, close and above to the analytic equilibrium.|+|Summary of paper |This paper studies the conditions where a population of agents reaches equilibrium in evolutionary game theory. An agent-based model is presented, where individuals compete for space using mixed strategies. The simulation of this model shows that the population’s mean strategy always converges to a stable state, close and above to the analytic equilibrium.|
 |Relevance to the track| Relevant to the Track| |Relevance to the track| Relevant to the Track|
 |Comments on relevance to the track| This paper is relevant to the ABM issue "Agent-based experimental economics".| |Comments on relevance to the track| This paper is relevant to the ABM issue "Agent-based experimental economics".|
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 |Detailed comments| Section 1, page 2: "Memorizing the last results is not practicable within this model, since the agent may not have the same opponent in its next confront." - however, agents could have been designed to memorize and apply the well succeeded strategies, whoever the opponents are, improving this way their satisfaction. Section 5, 1st paragraph: "The parameters chosen were: 3 as the number of descendants, 0.1% as the chance of mutation, and ±0.1 as the change in the inherited strategy, with 50% of probability of each, once the mutation is activated." - why these initial parameters? It lacks some explanation about these choices.| |Detailed comments| Section 1, page 2: "Memorizing the last results is not practicable within this model, since the agent may not have the same opponent in its next confront." - however, agents could have been designed to memorize and apply the well succeeded strategies, whoever the opponents are, improving this way their satisfaction. Section 5, 1st paragraph: "The parameters chosen were: 3 as the number of descendants, 0.1% as the chance of mutation, and ±0.1 as the change in the inherited strategy, with 50% of probability of each, once the mutation is activated." - why these initial parameters? It lacks some explanation about these choices.|
  
-Reviewer 2+==== Reviewer 2 ====
  
-|Summary of paper| The paper studies a model of evolutionary games on a grid. Agents compete when they are located in the same cell, through a chicken game. Each agent has a strategy defined by its probability to escalate or not. When the satisfaction of an agent is below a threshold, it moves to a random neighbouring cell. When the satisfaction of the agent is below another threshold, the agent leaves the game. The agents which are still in the game after a given number of time steps create several offspring which + 
-inherit the strategy of their father, with some mutation rate. The simulations show that the stationary state of the system include +|Summary of paper| The paper studies a model of evolutionary games on a grid. Agents compete when they are located in the same cell, through a chicken game. Each agent has a strategy defined by its probability to escalate or not. When the satisfaction of an agent is below a threshold, it moves to a random neighbouring cell. When the satisfaction of the agent is below another threshold, the agent leaves the game. The agents which are still in the game after a given number of time steps create several offspring which inherit the strategy of their father, with some mutation rate. The simulations show that the stationary state of the system include several strategies, and that the diversity of these strategies is higher when the mutation rate is high. This result is much richer than the theoretical stationary state in the standard game which includes only one strategy.|
-several strategies, and that the diversity of these strategies is higher when the mutation rate is high. This result is much richer than the theoretical stationary state in the standard game which includes only one strategy.|+
 |Relevance to the track| Relevant to the Track| |Relevance to the track| Relevant to the Track|
-Comments on relevance to the track| I think that the paper fits well the Social Simulation and Modelling track|+|Comments on relevance to the track| I think that the paper fits well the Social Simulation and Modelling track|
 |Originality |A direct extension of existing work| |Originality |A direct extension of existing work|
 |Literature awareness| Clear specification of relation to rest of field| |Literature awareness| Clear specification of relation to rest of field|
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 |Overall rating |Accept| |Overall rating |Accept|
 |Reviewer confidence|I'm very familiar with this area| |Reviewer confidence|I'm very familiar with this area|
-|Detailed comments|Interesting paper with clear results. Two criticisms however: - I think it is probably possible to derive an analytical model which predicts the proportion of strategies at the stationary state. To do this, you need to write the master equation ruling the fluxes between the different strategies, and I don't see any major difficulty for getting at least a good +|Detailed comments|Interesting paper with clear results. Two criticisms however: - I think it is probably possible to derive an analytical model which predicts the proportion of strategies at the stationary state. To do this, you need to write the master equation ruling the fluxes between the different strategies, and I don't see any major difficulty for getting at least a good approximation of this. Thus the affirmation that the result is only achievable through explicit simulation seems a bit dangerous to me.- the description of the local and global satisfactions, and their evolution lacks precision. Minor remark: In section 2, I don't understand the difference between pa (pb) and sa (sb). |
-approximation of this. Thus the affirmation that the result is only achievable through explicit simulation seems a bit dangerous to me.- the description of the local and global satisfactions, and their evolution lacks precision. Minor remark: In section 2, I don't understand the difference between pa (pb) and sa (sb). |+
  
-Masked Reviewer ID: Reviewer 3 +==== Reviewer 3 ==== 
-Review: + 
-Question + 
-Summary of paper +|Summary of paperThe paper presents an evolutionary extension of a previous work on a game played in a grid. The paper gives preliminary results on the experimentation showing a convergence towards the theoretical equilibrium in the context of the game when playing the 'chicken' payoff matrix.| 
-The paper presents an evolutionary extension of a previous work on a game +|Relevance to the track|Relevant to the Track| 
-played in a grid. The paper gives preliminary results on the +|Comments on relevance to the trackThe paper presents a number of experiments in full detail. It is a simulation of behaviour although the| 
-experimentation showing a convergence towards the theoretical equilibrium +|Originality |A direct extension of existing work| 
-in the context of the game when playing the 'chicken' payoff matrix. +|Comments on originality|The results are rather straightforward and largely result of the parameters choses. e.g. +-0.1 in the mutation determines how close the curve is to the theoretical equilibrium. If using the complete [0,1] range, the simulations would have shown an almost perfect equilibrium.| 
-Relevance to the +|Literature awareness|Clear specification of relation to rest of field| 
-track +|Scientific/technical soundnessBasically okay| 
-Relevant to the Track +|Significance of resultsPaper will moderately influence researchers close to the area| 
-Comments on +|Clarity of presentationBeautifully clear| 
-relevance to the +|Comments on clarity of presentation|Very nicely written paper.| 
-track +|Overall rating |Neutral| 
-The paper presents a number of experiments in full detail. It is a simulation +|Reviewer confidenceI'm moderately familiar with this area| 
-of behaviour although the +|Detailed commentsThe paper is a natural extension of the basic model allowing for an evolutionary approach very similar to the extansion that Axelrod did over the basic game to make it evolutionary. The paper is in that respect correct. However the results are very straightforward and differently from Axelrod's results, the experiments basically show that the game tends to the equilibrium. The fitness function 'determines' the solution and in that respect there is not much to be learned from the paper. The suggested changes for future work as expressed in the conclusion would not produce any non-expected result. The main conclusion that the convergence is 'over' the equilibrium is an artefact of the parameters used.|
-Originality A direct extension of existing work +
-Comments on +
-originality +
-The results are rather straightforward and largely result of the parameters +
-choses. e.g. +-0.1 in the mutation determines how close the curve is to the +
-theoretical equilibrium. If using the complete [0,1] range, the simulations +
-would have shown an almost perfect equilibrium. +
-Literature +
-awareness +
-Clear specification of relation to rest of field +
-Scientific/technical +
-soundness +
-Basically okay +
-Significance of +
-results +
-Paper will moderately influence researchers close to the area +
-Clarity of +
-presentation +
-Beautifully clear +
-Comments on +
-clarity of +
-presentation +
-Very nicely written paper. +
-Overall rating Neutral +
-Reviewer +
-confidence +
-I'm moderately familiar with this area +
-Detailed +
-comments +
-The paper is a natural extension of the basic model allowing for an +
-evolutionary approach very similar to the extansion that Axelrod did over +
-the basic game to make it evolutionary. The paper is in that respect correct. +
-However the results are very straightforward and differently from Axelrod's +
-results, the experiments basically show that the game tends to the +
-equilibrium. The fitness function 'determines' the solution and in that +
-respect there is not much to be learned from the paper. The suggested +
-changes for future work as expressed in the conclusion would not produce +
-Reviews For Paper https://cmt.research.microsoft.com/EPIA2009/Protected/Author/ViewR... +
-3 de 4 15/06/2009 17:03 +
-any non-expected result. The main conclusion that the convergence is +
-'over' the equilibrium is an artefact of the parameters used. +
-Reviews For Paper https://cmt.research.microsoft.com/EPIA2009/Protected/Author/ViewR... +
-4 de 4 15/06/2009 17:03+
  
  
geopro/pedro/evolucao.1247582196.txt.gz · Última modificação: 2009/07/14 14:36 por pedro