African Perspectives on Progress and Challenges in Agricultural Transformation

International Development, Downloads July 2008 - June 2009: 9,

PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games

In recent years, Game AI research has made important breakthroughs using Reinforcement Learning (RL). Despite this, RL for modern tabletop games has gained little to no attention, even when they offer a range of unique challenges compared to video games. To bridge this gap, we introduce PyTAG, a Python API for interacting with the Tabletop Games framework (TAG). TAG contains a growing set of more than 20 modern tabletop games, with a common API for AI agents. We present techniques for training RL agents in these games and introduce baseline results after training Proximal Policy Optimisation algorithms on a subset of games. Finally, we discuss the unique challenges complex modern tabletop games provide, now open to RL research through PyTAG

Economics, Agency, and Causal Explanation

The paper considers three questions. First, what is the connection between economics and agency? It is argued that causation and explanation in economics fundamentally depend on agency. So a philosophical understanding of economic explanation must be sensitive to an understanding of agency. Second, what is the connection between agency and causation? A causal view of agency-involving explanation is defended against a number of arguments from the resurgent noncausalist tradition in the literature on agency and action-explanation. If agency is fundamental to economic explanation, it is argued, then so is causation. Third, what is the connection between causal explanation and the natural sciences? It is argued that, though the explanations given in economics and other social sciences are causal explanations, they are different in kind from the causal explanations of the natural sciences. On the one hand, then, the causal explanations of the social sciences are irreducible to those found in the natural sciences. On the other hand, the causal relations described by the social sciences are not completely autonomous; they do not float free of, or operate independently from, the causal relations charted by the natural sciences

Leibniz, Acosmism, and Incompossibility

Leibniz claims that God acts in the best possible way, and that this includes creating exactly one world. But worlds are aggregates, and aggregates have a low degree of reality or metaphysical perfection, perhaps none at all. This is Leibniz’s tendency toward acosmism, or the view that there this no such thing as creation-as-a-whole. Many interpreters reconcile Leibniz’s acosmist tendency with the high value of worlds by proposing that God sums the value of each substance created, so that the best world is just the world with the most substances. I call this way of determining the value of a world the Additive Theory of Value (ATV), and argue that it leads to the current and insoluble form of the problem of incompossibility. To avoid the problem, I read “possible worlds” in “God chooses the best of all possible worlds” as referring to God’s ideas of worlds. These ideas, though built up from essences, are themselves unities and so well suited to be the value bearers that Leibniz’s theodicy requires. They have their own value, thanks to their unity, and that unity is not preserved when more essences are added

Standing in a Garden of Forking Paths

According to the Path Principle, it is permissible to expand your set of beliefs iff (and because) the evidence you possess provides adequate support for such beliefs. If there is no path from here to there, you cannot add a belief to your belief set. If some thinker with the same type of evidential support has a path that they can take, so do you. The paths exist because of the evidence you possess and the support it provides. Evidential support grounds propositional justification. The principle is mistaken. There are permissible steps you may take that others may not even if you have the very same evidence. There are permissible steps that you cannot take that others can even if your beliefs receive the same type of evidential support. Because we have to assume almost nothing about the nature of evidential support to establish these results, we should reject evidentialism

Proprietary Reasons and Joint Action

Some of the reasons one acts on in joint action are shared with fellow participants. But others are proprietary: reasons of one’s own that have no direct practical significance for other participants. The compatibility of joint action with proprietary reasons serves to distinguish the former from other forms of collective agency; moreover, it is arguably a desirable feature of joint action. Advocates of “team reasoning” link the special collective intention individual participants have when acting together with a distinctive form of practical reasoning that purports to put individuals in touch with group or collective reasons. Such views entail the surprising conclusion that one cannot engage in joint action for proprietary reasons. Suppose we understand the contrast between minimal and robust forms of joint action in terms of the extent to which participants act on proprietary reasons as opposed to shared reasons. Then, if the team reasoning view of joint intention and action is correct, it makes no sense to talk of minimal joint action. As soon as the reason for which one participates is proprietary, then one is not, on this view, genuinely engaged in joint action