Deacon has suggested that one of the key factors of language evolution is not characterized by an increase in genetic contribution, often known as the Baldwin effect, but rather by a decrease. This process effectively increases linguistic learning capability by organizing a novel synergy of multiple lower-order functions previously irrelevant to the process of language acquisition. Deacon posits that this transition is not caused by natural selection. Rather, it is due to the relaxation of natural selection. While there are some cases in which relaxation caused by some external factors indeed induces the transition, we do not know what kind of relaxation has worked in language evolution. In this article, a genetic-algorithm-based computer simulation is used to investigate how the niche-constructing aspect of linguistic behavior may trigger the degradation of genetic predisposition related to language learning. The results show that agents initially increase their genetic predisposition for language learning—the Baldwin effect. They create a highly uniform sociolinguistic environment—a linguistic niche construction. This means that later generations constantly receive very similar inputs from adult agents, and subsequently the selective pressure to retain the genetic predisposition is relaxed.

This paper studies the characteristics of a new composite evolutionary computation algorithm in which genetic evolution, individual learning and social learning interact in NK fitness landscape. We derive conditions for effective social learning in static and dynamic environments using computer sim ulations of a model of the composite evolutionary algorithm. The conditions for static environments are: the individual learning cost should be at least 1.5 times than the social one; the mutation rate should be less than 0.04 per each gene; more than 3 genes should not interact. These conditions qualitatively mean that: the individual learning cost is larger than the social learning cost; teaching is beneficial for teachers; mutation rate is not too high, must be smaller than error thresold; the fitness landscape is not so complex. We also show that this algorithm is effective in dynamic environments in which NK fitness landscape changes with time, if these conditions are satisfied. Frequent environmental change favors social learning, but under more severe conditions, such as high epistasis and higher mutation rate than the error threshold, individual learning is more useful in finding better solutions.

In this paper, we consider a issue that the reliable and the inexpensive communication method in swarm robotics. The ants forage for preys by using pheromone trails. They lay down the pheromone trails between preys and a nest. By detecting the trail pheromone, they can find the preys. Though they do not have excellent intelligence, they can communicate with each other and cooperate by adding information to the environment, like a pheromone. This communication method has a merit that an agent does not need to memorize the place of the preys. We consider to answer the issue that ldquoHow do the swarm robots communicate using pheromone trail?rdquo. We construct a swarm behavior simulator and develop swarm robots that communicate using the pheromone trail. We demonstrate the effectiveness of the communication using the pheromone trail by computer simulations and experiments using swarm robots. To realize this purpose, we design a swarm behavior algorithm, based on 4 perceptual signs (stimuli) and 3 effector signs (actions). In the simulations, an experimental field is discretized by computational grids, and evaporation and diffusion are phenomena of the pheromone modeled by discretized equations. The proposed algorithm is demonstrated by the simulation. Simulation result shows that proposed algorithms act effectively. Based on the simulation results, we set three robots, one nest and one prey in the flat experimental field. We observe three robotspsila behavior and the state of the environment for 20 minutes. The robots laid down the pheromone trail between the nest and the prey, and reinforced the pheromone trail many times. This fact means that swarm robots can realize the function of the chemical, indirect, plastic and local communication like ants by using the pheromone trail.

One of the most important technical problems in reliable multicast protocol is to reduce redundant control packets and retransmitted packets. An approach for reducing them by making use of newly-invented network architecture, the active network technology, has been proposed. In the paper we compare a network-initiated approach, i.e. a reliable multicast protocol with network support, and conventional end-to-end approaches. These are compared under more realistic situations such as part of routers are equipped with the newly-invented active network technology. Our simulation results show that the network-initiated approach with 15% active routers outperforms conventional end-to-end approaches from the viewpoint of scalability. We also investigate the desirable location of active routers with a sophisticated network topology model, Tiers model, which reflects hierarchical structure of the Internet. Our simulation results suggest that at first active routers should be implemented in WANs because delay performance can be improved with a small number of active routers. After active routers are broadly implemented in WAN, the policy for location of active routers should be switched to MAN with expecting a decrease of redundant NAK transmission inside a network.

Starting with a brief review on the single-electron memory and its significance among various single-electron devices, this paper addresses the key issues which one inevitably encounters when one tries to achieve giga-to-tera bit memory integration. Among the issues discussed are: room-temperature operation; memory-cell architecture; sensing scheme; cell-design guideline; use of nanocrystalline silicon versus lithography; array architecture; device-to-device variations; read/write error rate; and CMOS/single-electron-memory hybrid integration and its positioning among various memory architectures.

Self-reproduction via description is discussed in a network model of machines and description tapes. Tapes consist of bit strings, which encode the machines' function. A tape is replicated when it is read by adequate machines. Generally, a machine rewrites a tape without doing correct replication. The variation in a reproduced tape is taken as mutation. Because this mutation is caused by a machine's program, we call it active mutation. Which machine is translated from a given tape is dependent on what kind of a machine reads the tape. External noise is introduced in a machine's reading process to make errors. A new reaction pathway is induced by external noise via a machine's error action. We find that the induced pathways will be mimicked deterministically in an emerging core structure. This core structure will remain stable after turning off external noise. Low external noise develops a core structure of a minimal self-replicative loop. When external noise is elevated, a more complex network evolves. Machines containing a complex core network, which has been bred in high external noise, will actively rewrite tapes rather than just replicate them. Self-replication not as an individual but as a network now becomes important.

This paper proposes and examines some architectural features suitable for micro-vectorprocessors. Due to the I/O-pin bottleneck, micro-vectorprocessors should save the off-chip memory bandwidth by exploiting the on-chip register bandwidth instead. Those features include the vector-instruction-level multithreading and FIFO vector registers. There are three variations of multithreading:periodic, forced, and round-robin. The paper also formulates the performance of micro-vectorprocessors with such architectural features. And then, the paper evaluates the performance attainable by those micro-vectorprocessors with such architectural features. And then, the paper evaluates the performance attainable by those micro-vectorprocessors through software simulation. From the benchmark results, it is found that the vector-instruction-level multithreading and FIFO vector registers can improve the performance of the micro-vectorprocessors with the half memory bandwidth comparable to that of ones with the full memory bandwidth. Furthermore, forced multithreading is found to be tolerant to the large memory access latency. From these results, the paper concludes that the forced multithreading at the vector-instruction level is a good candidate for the architectural features suitable to micro-vectorprocessors.

This paper presents the benchmark results on a vector-processor prototype based on the MSFV (multithreaded streaming/FIFO vector) architecture. The MSFV architecture is single-chip oriented, and thus its main object is to save the off-chip memory bandwidth by exploiting the register bandwidth instead. The register bandwidth is exploited by the synergism of FIFO register, chaining, streaming, and multithreading. This paper tries to identify the strength and weakness of those architectural features. The results for basic vector operations and Livermore Fortran Kernels are reported in terms of normalized FLOPC (floating-point operations per clock cycle) and compared to previously-reported results on the Cray X-MP, Y-MP, Fujitsu VP-200, Hitachi S-810/20, NEC SX-2, and SX-3. These comparisons show that, for many basic vector operations, the execution rate of the MSFV prototype results in worst due to its saving the memory bandwidth. However, for Livermore Fortran Kernels, the MSFV prototype results in worst due to its saving the memory bandwidth. However, for Livermore Fortran Kernels, the MSFV prototype outperforms the VP-200 by 2.11 times (geometric mean) and one processor of the X-MP by 1.22 times (geometric mean) in terms of FLOPC. Also, it is 0.67 times (geometric mean) faster than the S-810/20, and 0.76 times (geometric mean) faster than the SX-2. The paper concludes that the MSFV architecture is successful in saving the memory bandwidth.