What are some of the best practices and resources for learning and teaching game theory and networks?

1 Understand the basics

Before diving into the advanced concepts and applications of game theory and networks, you need to have a solid grasp of the basic elements and tools. For game theory, this means learning how to model and analyze games using payoff matrices, decision trees, Nash equilibria, dominant and dominated strategies, and mixed strategies. For networks, this means learning how to represent and measure networks using nodes, edges, adjacency matrices, centrality, density, and clustering. You can find many online tutorials, videos, and books that explain these concepts in an intuitive and accessible way, such as the ones by Khan Academy, Coursera, or MIT OpenCourseWare.

2 Apply to real-world examples

One of the best ways to learn and teach game theory and networks is to apply them to real-world examples that illustrate their relevance and usefulness. For example, you can use game theory to understand how people cooperate or compete in social dilemmas, such as the prisoner's dilemma, the public goods game, or the ultimatum game. You can also use game theory to analyze how firms, politicians, or countries interact in markets, elections, or wars. Similarly, you can use networks to understand how information, diseases, or influence spread in social media, epidemics, or social movements. You can also use networks to explore how patterns, structures, and dynamics emerge in biological, ecological, or technological systems. You can find many case studies, simulations, and experiments that demonstrate these applications, such as the ones by The Game Theorist, NetLogo, or The NetSci High.

3 Explore the connections and extensions

Another way to enrich your learning and teaching of game theory and networks is to explore the connections and extensions that link these fields to other disciplines and topics. For example, you can learn how game theory and networks can be combined to study network games, where the payoffs and strategies of players depend on the network structure and the actions of their neighbors. You can also learn how game theory and networks can be extended to incorporate uncertainty, learning, evolution, behavior, and cognition. You can find many interdisciplinary courses, papers, and books that cover these connections and extensions, such as the ones by Stanford Online, The Santa Fe Institute, or The Society for Mathematical Biology.

4 Practice with exercises and projects

To master game theory and networks, you need to practice with exercises and projects that challenge your understanding and skills. For game theory, this means solving problems that require you to find the optimal strategies and outcomes for different types of games, such as simultaneous, sequential, repeated, or cooperative games. For networks, this means analyzing data and visualizing networks that require you to use the appropriate methods and tools, such as graph theory, network analysis, or network science. You can find many online platforms, software, and datasets that offer these exercises and projects, such as the ones by Brilliant, Gephi, or SNAP.

5 Engage with the community

Finally, one of the most rewarding and enjoyable ways to learn and teach game theory and networks is to engage with the community of researchers, educators, and enthusiasts who share your passion and curiosity. You can join online forums, blogs, podcasts, or newsletters that discuss the latest developments, insights, and questions in these fields. You can also participate in online events, workshops, or competitions that offer opportunities to network, collaborate, and showcase your work. You can find many online communities and resources that foster these engagements, such as the ones by Reddit, The Game Theory Podcast, or The Network Science Society.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?