This research presents an exploration of a post-anthropocentric perspective towards the design of human-agent interaction (HAI), observed through the development of a wearable device prototype. The device argues for an alternative stance towards the orthodox human-centered perspectives in HAI executed through human-computer interaction (HCI). Taking a research through design approach the device presents a speculative scenario of agential interaction in the form of a perceptual companion interface. It overlaps with post-anthropocentric philosophical discourse around the phenomenon of agential perception present in contemporary imaginings of HCI. The prototype intends to act as a catalyst for imagining post-anthropocentric agential interactions within HAI.

Reuse distance (i.e. LRU stack distance) precisely characterizes program locality and has been a basic tool for memory system research since the 1970s. However, the high cost of measuring has restricted its practical uses in performance debugging, locality analysis and optimizations of long-running applications.In this work, we improve the efficiency by exploring the connection between time and locality. We propose a statistical model that converts cheaply obtained time distance to the more costly reuse distance. Compared to the state-of-the-art technique, this approach reduces measuring time by a factor of 17, and approximates cache line reuses with over 99% accuracy and the cache miss rate with less than 0.4% average error for 12 SPEC 2000 integer and floating-point benchmarks. By exploiting the strong correlations between time and locality, this work makes precise locality as easy to obtain as data access frequency, and opens new opportunities for program optimizations.