Stateman: Using Metafunctions to Manage Large Terms Representing Machine States

Stateman: Using Metafunctions to Manage Large Terms Representing Machine States

When ACL2 is used to model the operational semantics of computing machines, machine states are typically represented by terms recording the contents of the state components. When models are realistic and are stepped through thousands of machine cycles, these terms can grow quite large and the cost of simplifying them on each step grows. In this paper we describe an ACL2 book that uses HIDE and ...

Using Machine Learning to Retrieve and Manage Internet Information

Representing Reach-to-Grasp Trajectories Using Perturbed Goal Motor States

In the biological system which controls movements of the hand and arm, there is no clear distinction between movement planning and movement execution: the details of the hand’s trajectory towards a target are computed ‘online’, while the movement is under way. At the same time, human agents can reach for a target object in several discretely different ways, which have their own distinctive traj...

From HOTs to Self-Representing States

According to David Rosenthal, a mental state is conscious just in case its subject suitably represents herself as being in that state, where this entails that the mental state " is accompanied by a noninferential, nondispositional, assertoric thought to the effect that one is in that very state " (2002a, p. 410; see also Rosenthal, 1997, p. 742). This assertoric thought, since it is about anoth...

Translation of Patent Sentences with a Large Vocabulary of Technical Terms Using Neural Machine Translation

Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT). Despite its recent success, NMT cannot handle a larger vocabulary because training complexity and decoding complexity proportionally increase with the number of target words. This problem becomes even...