7048039
Establishing Communication Systems without Explicit Meaning Transmission
This paper investigates the development of experience-based meaning creation and explores the problem of establishing successful communication systems in a population of agents. The aim of the work is to investigate how such systems can develop, without reliance on phenomena not found in actual human language learning, such as the explicit transmission of meaning or the provision of reliable error feedback to guide learning. Agents develop individual, distinct meaning structures, and although they can communicate despite this, communicative success is closely related to the proportion of shared lexicalised meaning, and the communicative systems have a large degree of redundant synonymy.
18711767
Semantic Generalisation and the Inference of Meaning
In this paper, a computational model of a successful negotiated communication system is presented, in which language agents develop their own meanings in response to their environment and attempt to infer the meanings of others’ utterances. The inherent uncertainty in the process of meaning inference in the system leads to variation in the agents’ internal semantic representations, which then itself drives language change in the form of semantic generalisation.
314094
Correcting errors without leaking partial information
This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W --- that is, from the adversary's point of view, the entropy of W will drop significantly. Nevertheless, we construct schemes with which Alice and Bob can prevent an adversary from learning any useful information about W. Specifically, if the entropy of W is sufficiently high, then there is no function f(W) which the adversary can learn from the error-correction information with significant probability.This leads to several new results: (a) the design of noise-tolerant "perfectly one-way" hash functions in the sense of Canetti et al. [7], which in turn leads to obfuscation of proximity queries for high entropy secrets W; (b) private fuzzy extractors [11], which allow one to extract uniformly random bits from noisy and nonuniform data W, while also insuring that no sensitive information about W is leaked; and (c) noise tolerance and stateless key re-use in the Bounded Storage Model, resolving the main open problem of Ding [10].The heart of our constructions is the design of strong randomness extractors with the property that the source W can be recovered from the extracted randomness and any string W' which is close to W.
2433417
Logarithmic Opinion Pools for Conditional Random Fields
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation to counter the tendency of these models to overfit. The standard approach to regularising CRFs involves a prior distribution over the model parameters, typically requiring search over a hyperparameter space. In this paper we address the overfitting problem from a different perspective, by factoring the CRF distribution into a weighted product of individual "expert" CRF distributions. We call this model a logarithmic opinion pool (LOP) of CRFs (LOP-CRFs). We apply the LOP-CRF to two sequencing tasks. Our results show that unregularised expert CRFs with an unregularised CRF under a LOP can outperform the unregularised CRF, and attain a performance level close to the regularised CRF. LOP-CRFs therefore provide a viable alternative to CRF regularisation without the need for hyperparameter search.
13326296
Integrated Facility Design Using an Evolutionary Approach with a Subordinate Network Algorithm
The facility design problem is a common one in manufacturing and service industries and has been studied extensively in the literature. However, restrictions on the scope of the design problem have been imposed by the limitations of the optimization techniques employed. This paper uses an evolutionary approach with a subordinate network optimization algorithm to produce integrated designs that have better translations into physical plant designs. A new distance metric to consider material travel along the perimeter of the departments to and from input/output locations is devised. This perimeter distance metric is used in the objective function to produce facility designs that simultaneously optimize design of department shapes, department placement and location of the department input/output points.
278372
CPU Cache Prefetching: Timing Evaluation of Hardware Implementations
Prefetching into CPU caches has long been known to be effective in reducing the cache miss ratio, but known implementations of prefetching have been unsuccessful in improving CPU performance. The reasons for this are that prefetches interfere with normal cache operations by making cache address and data ports busy, the memory bus busy, the memory banks busy, and by not necessarily being complete by the time that the prefetched data is actually referenced. In this paper, we present extensive quantitative results of a detailed cycle-by-cycle trace-driven simulation of a uniprocessor memory system in which we vary most of the relevant parameters in order to determine when and if hardware prefetching is useful. We find that, in order for prefetching to actually improve performance, the address array needs to be double ported and the data array needs to either be double ported or fully buffered. It is also very helpful for the bus to be very wide (e.g., 16 bytes) for bus transactions to be split and for main memory to be interleaved. Under the best circumstances, i.e., with a significant investment in extra hardware, prefetching can significantly improve performance. For implementations without adequate hardware, prefetching often decreases performance.
5725147
Local search genetic algorithm for optimal design of reliable networks
This paper presents a genetic algorithm (GA) with specialized encoding, initialization, and local search operators to optimize the design of communication network topologies. This NP-hard problem is often highly constrained so that random initialization and standard genetic operators usually generate infeasible networks. Another complication is that the fitness function involves calculating the all-terminal reliability of the network, which is a computationally expensive calculation. Therefore, it is imperative that the search balances the need to thoroughly explore the boundary between feasible and infeasible networks, along with calculating fitness on only the most promising candidate networks. The algorithm results are compared to optimum results found by branch and bound and also to GA results without local search operators on a suite of 79 test problems. This strategy of employing bounds, simple heuristic checks, and problem-specific repair and local search operators can be used on other highly constrained combinatorial applications where numerous fitness calculations are prohibitive.