Efficient, Safe, and Probably Approximately Complete Learning of Action Models

In this paper we explore the theoretical boundaries of planning in a setting where no model of the agent's actions is given. Instead of an action model, a set of successfully executed plans are given and the task is to generate a plan that is safe, i.e., guaranteed to achieve the goal without failing. To this end, we show how to learn a conservative model of the world in which actions are guaranteed to be applicable. This conservative model is then given to an off-the-shelf classical planner, resulting in a plan that is guaranteed to achieve the goal. However, this reduction from a model-free planning to a model-based planning is not complete: in some cases a plan will not be found even when such exists. We analyze the relation between the number of observed plans and the likelihood that our conservative approach will indeed fail to solve a solvable problem. Our analysis show that the number of trajectories needed scales gracefully

The Price of Uncertain Priors in Source Coding

We consider the problem of one-way communication when the recipient does not know exactly the distribution that the messages are drawn from, but has a "prior" distribution that is known to be close to the source distribution, a problem first considered by Juba et al. We consider the question of how much longer the messages need to be in order to cope with the uncertainty about the receiver's prior and the source distribution, respectively, as compared to the standard source coding problem. We consider two variants of this uncertain priors problem: the original setting of Juba et al. in which the receiver is required to correctly recover the message with probability 1, and a setting introduced by Haramaty and Sudan, in which the receiver is permitted to fail with some probability $\epsilon$. In both settings, we obtain lower bounds that are tight up to logarithmically smaller terms. In the latter setting, we furthermore present a variant of the coding scheme of Juba et al. with an overhead of $\log\alpha+\log 1/\epsilon+1$ bits, thus also establishing the nearly tight upper bound.Comment: To appear in IEEE Transactions on Information Theor

User's guide to the UTIL-ODRC tape processing program

The UTIL-ODRC computer compatible tape processing program, its input/output requirements, and its interface with the EXEC 8 operating system are described. It is a multipurpose orbital data reduction center (ODRC) tape processing program enabling the user to create either exact duplicate tapes and/or tapes in SINDA/HISTRY format. Input data elements for PRAMPT/FLOPLT and/or BATCH PLOT programs, a temperature summary, and a printed summary can also be produced

Access to Population-Level Signaling as a Source of Inequality

We identify and explore differential access to population-level signaling (also known as information design) as a source of unequal access to opportunity. A population-level signaler has potentially noisy observations of a binary type for each member of a population and, based on this, produces a signal about each member. A decision-maker infers types from signals and accepts those individuals whose type is high in expectation. We assume the signaler of the disadvantaged population reveals her observations to the decision-maker, whereas the signaler of the advantaged population forms signals strategically. We study the expected utility of the populations as measured by the fraction of accepted members, as well as the false positive rates (FPR) and false negative rates (FNR). We first show the intuitive results that for a fixed environment, the advantaged population has higher expected utility, higher FPR, and lower FNR, than the disadvantaged one (despite having identical population quality), and that more accurate observations improve the expected utility of the advantaged population while harming that of the disadvantaged one. We next explore the introduction of a publicly-observable signal, such as a test score, as a potential intervention. Our main finding is that this natural intervention, intended to reduce the inequality between the populations' utilities, may actually exacerbate it in settings where observations and test scores are noisy

Development of a CRAY 1 version of the SINDA program

The SINDA thermal analyzer program was transferred from the UNIVAC 1110 computer to a CYBER And then to a CRAY 1. Significant changes to the code of the program were required in order to execute efficiently on the CYBER and CRAY. The program was tested on the CRAY using a thermal math model of the shuttle which was too large to run on either the UNIVAC or CYBER. An effort was then begun to further modify the code of SINDA in order to make effective use of the vector capabilities of the CRAY