Robots are often used in long-duration scenarios, such as on the surface of Mars,where they may need to adapt to environmental changes. Typically, robots have been built specifically for single tasks, such as moving boxes in a warehouse or surveying construction sites. However, there is a modern trend away from human hand-engineering and toward robot learning. To this end, the ideal robot is not engineered,but automatically designed for a specific task. This thesis focuses on robots which learn path-planning algorithms for specific environments. Learning is accomplished via genetic programming. Path-planners are represented as Python code, which is optimized via Pareto evolution. These planners are encouraged to explore curiously and efficiently. This research asks the questions: “How can robots exhibit life-long learning where they adapt to changing environments in a robust way?”, and “How can robots learn to be curious?”.

The right to cast a meaningful vote, equal in value to other votes, is a fundamental tenet US elections. Despite the 1964 Supreme Court decision formally establishing the one person, one vote principle as a legal requirement of elections, our democracy consistently falls short of it. With mechanisms including the winner-take-all format in the Electoral College, disproportioned geographic allocation of senators, extreme partisan gerrymandering in the House of Representatives, and first-past-the-post elections, many voters experience severe vote dilution. <br/><br/>In order to legitimize our democratic structures, American elections should be reformed so every person’s vote has equal weight, ensuring that the election outcomes reflect the will of the people. Altering the current election structure to include more proportional structures including rank choice voting and population-based representation, will result in a democracy more compatible with the one person, one vote principle.

Since the global financial crisis of 2007-8, interest in worker-cooperatives and alternative forms of organization has surged. Mondragon, located in the Basque region of Spain, represents the largest federation of worker-cooperatives around the world, consisting of 98 cooperatives and 143 subsidiaries, which earned a total revenue of $14.5 billion in 2019. While previous attempts to establish a similar model have historically reached limited success, Mondragon has achieved a unique balance of remaining economically viable, on the one hand, and staying true to its founding principles of democratic governance, on the other. This paper sets out to analyze the democratic structure and the cooperative culture at the heart of the Mondragon model, as well as the new type of human relationship that it fosters. In particular, this relationship is one in which individual well-being is bound up with communal well-being that avoids the antagonistic clash between the capital and labor.