Conversational adequacy: mistakes are the essence

Conversational adequacy: mistakes are the essence

We argue that meta-dialog and meta-reasoning, far from being of only occasional use, are the very essence of conversation and communication between agents. We give four paradigm examples of massive use of meta-dialog where only limited object dialog may be present, and use these to bolster our claim of centrality for meta-dialog. We further illustrate this with related work in active logics. We...

Towards domain-independent, task-oriented, conversational adequacy

Past approaches for solving MDPs have several weaknesses: 1) Decision-theoretic computation over the state space can yield optimal results but scales poorly. 2) Value-function approximation typically requires human-specified basis functions and has not been shown successful on nominal (“discrete”) domains such as those in the ICAPS planning competitions. 3) Replanning by applying a classical pl...

Mistakes are lessons of the past.

Web-based Presentation of Information: The Top Ten Mistakes and Why They Are Mistakes

This paper describes ten of the most common mistakes, from a human-factors or usability perspective, in presenting information on the web. The ten mistakes are: (1) burying information too deep in a website, (2) overloading pages with too much material, (3) providing awkward or confusing navigation, (4) putting information in unexpected places on the page, (5) not making links obvious and clear...

How random are a learner's mistakes?

Given a random binary sequence $X^{(n)}$ of random variables, $X_{t},$ $t=1,2,...,n$, for instance, one that is generated by a Markov source (teacher) of order $k^{*}$ (each state represented by $k^{*}$ bits). Assume that the probability of the event $X_{t}=1$ is constant and denote it by $\beta$. Consider a learner which is based on a parametric model, for instance a Markov model of order $k$,...