Option Transfer and SMDP Abstraction with Successor Features

Abstraction plays an important role in the generalisation of knowledge and skills and is key to sample efficient learning. In this work, we study joint temporal and state abstraction in reinforcement learning, where temporally-extended actions in the form of options induce temporal abstractions, while aggregation of similar states with respect to abstract options induces state abstractions. Many existing abstraction schemes ignore the interplay of state and temporal abstraction. Consequently, the considered option policies often cannot be directly transferred to new environments due to changes in the state space and transition dynamics. To address this issue, we propose a novel abstraction scheme building on successor features. This includes an algorithm for transferring abstract options across different environments and a state abstraction mechanism that allows us to perform efficient planning with the transferred options.Comment: IJCAI 2022 (Long paper

The Impact of Real Options on Willingness to Pay for Investments in Road Safety

Abstract: Public investments are dynamic in nature, and decision making must account for the uncertainty, irreversibility and potential for future learning. In this paper we adapt the theory for investment under uncertainty for a public referendum setting and perform the first empirical test to show that estimates of the value of safety (VSL) from stated preference surveys are highly dependent on the inclusion of the option value. Our results indicate an option value of a major economic magnitude. This implies that previously reported VSL estimates are exaggerated.Value of a Statistical Life; Real Options; Contingent Valuation; Road Safety

The stories that documents tell: changing technology options from Blackboard, Webfuse and the content management system at Central Queensland University

[Abstract]: This paper analyses selected documents written about, and for, three of Central Queensland University's educational technologies and what those documents say about current issues and strategies in the technologies supporting teaching and learning at the university. The paper draws four significant implications from this analysis. Using the stories that documents tell to learn from changing technology options for teaching and learning innovations requires attentiveness to, and an engagement with, these implications