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Welcome to the documentation for the Axelrod Python library — Axelrod 0.0.1 documentation

Welcome to the documentation for the Axelrod Python library. Welcome to the documentation for the Axelrod Python library. Here is quick overview of the current capabilities of the library:. Over 100 strategies from the literature and some exciting original contributions. Classic strategies like TiT-For-Tat, WSLS, and variants. Zero-Determinant and other Memory-One strategies. Strategy transformers that augment the abilities of any strategy. Round Robin tournaments with a variety of options, including:.

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Welcome to the documentation for the Axelrod Python library — Axelrod 0.0.1 documentation | axelrod.readthedocs.io Reviews

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Welcome to the documentation for the Axelrod Python library. Welcome to the documentation for the Axelrod Python library. Here is quick overview of the current capabilities of the library:. Over 100 strategies from the literature and some exciting original contributions. Classic strategies like TiT-For-Tat, WSLS, and variants. Zero-Determinant and other Memory-One strategies. Strategy transformers that augment the abilities of any strategy. Round Robin tournaments with a variety of options, including:.

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2 latest

3 tutorials

4 reference

5 community

6 citing the library

7 docs

8 raquo;

9 edit on github

10 head to head matches

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Welcome to the documentation for the Axelrod Python library — Axelrod 0.0.1 documentation | axelrod.readthedocs.io Reviews

https://axelrod.readthedocs.io

Welcome to the documentation for the Axelrod Python library. Welcome to the documentation for the Axelrod Python library. Here is quick overview of the current capabilities of the library:. Over 100 strategies from the literature and some exciting original contributions. Classic strategies like TiT-For-Tat, WSLS, and variants. Zero-Determinant and other Memory-One strategies. Strategy transformers that augment the abilities of any strategy. Round Robin tournaments with a variety of options, including:.

INTERNAL PAGES

axelrod.readthedocs.io

1

Research topics — Axelrod 0.0.1 documentation

http://axelrod.readthedocs.io/en/latest/tutorials/further_topics/index.html

New to Game Theory and/or Python. Further capabilities in the library. Background to Axelrod’s Tournament. Play Contexts and Generic Prisoner’s Dilemma. Part of the team. This section contains descriptions of particular tools of interest to those doing game theoretic research. Provided by Read the Docs. On Read the Docs. Free document hosting provided by Read the Docs.

2

Noisy tournaments — Axelrod 0.0.1 documentation

http://axelrod.readthedocs.io/en/latest/tutorials/further_topics/noisy_tournaments.html

New to Game Theory and/or Python. Further capabilities in the library. Background to Axelrod’s Tournament. Play Contexts and Generic Prisoner’s Dilemma. Part of the team. A common variation on iterated prisoner’s dilemma tournaments is to add stochasticity in the choice of actions, simply called noise. This noise is introduced by flipping plays between ‘C’ and ‘D’ with some probability that is applied to all plays after they are delivered by the player. Would usually cooperate well with itself:.

3

Human Interaction — Axelrod 0.0.1 documentation

http://axelrod.readthedocs.io/en/latest/tutorials/getting_started/human_interaction.html

New to Game Theory and/or Python. Further capabilities in the library. Background to Axelrod’s Tournament. Play Contexts and Generic Prisoner’s Dilemma. Part of the team. New to Game Theory and/or Python. It is possible to play interactively using the Human strategy:. You will be prompted for the action to play at each turn:. Starting new match Turn 1. Me: C Turn 1: me played C, opponent played C Turn 2. Me: D Turn 2: me played D, opponent played C Turn 3. After this, the. Provided by Read the Docs.

4

Probabilistic Ending Tournaments — Axelrod 0.0.1 documentation

http://axelrod.readthedocs.io/en/latest/tutorials/further_topics/probabilistict_end_tournaments.html

New to Game Theory and/or Python. Further capabilities in the library. Background to Axelrod’s Tournament. Play Contexts and Generic Prisoner’s Dilemma. Part of the team. It is possible to create a tournament where the length of each Match is not constant for all encounters: after each turn the Match ends with a given probability:. We can view the results in a similar way as described in Accessing tournament results. 30, 00, 3.0, 3.0]. 50, 10, 3.7, 3.6]. 30, 03, 3.0, 3.0]. 30, 04, 3.0, 3.0].

5

Tutorials — Axelrod 0.0.1 documentation

http://axelrod.readthedocs.io/en/latest/tutorials/index.html

New to Game Theory and/or Python. Further capabilities in the library. Background to Axelrod’s Tournament. Play Contexts and Generic Prisoner’s Dilemma. Part of the team. This section contains a variety of tutorials related to the Axelrod library. New to Game Theory and/or Python. Creating and running a simple tournament. Further capabilities in the library. Build new types of tournaments. Reading and writing interactions from/to file. Setting a random seed. Contributing to the library. On Read the Docs.

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axelrod.readthedocs.io

Welcome to the documentation for the Axelrod Python library — Axelrod 0.0.1 documentation

Welcome to the documentation for the Axelrod Python library. Welcome to the documentation for the Axelrod Python library. Here is quick overview of the current capabilities of the library:. Over 100 strategies from the literature and some exciting original contributions. Classic strategies like TiT-For-Tat, WSLS, and variants. Zero-Determinant and other Memory-One strategies. Strategy transformers that augment the abilities of any strategy. Round Robin tournaments with a variety of options, including:.

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