21 research outputs found
Augmenting Agent Platforms to Facilitate Conversation Reasoning
Within Multi Agent Systems, communication by means of Agent Communication
Languages (ACLs) has a key role to play in the co-operation, co-ordination and
knowledge-sharing between agents. Despite this, complex reasoning about agent
messaging, and specifically about conversations between agents, tends not to
have widespread support amongst general-purpose agent programming languages.
ACRE (Agent Communication Reasoning Engine) aims to complement the existing
logical reasoning capabilities of agent programming languages with the
capability of reasoning about complex interaction protocols in order to
facilitate conversations between agents. This paper outlines the aims of the
ACRE project and gives details of the functioning of a prototype implementation
within the Agent Factory multi agent framework
Global maps of soil temperature.
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications
Measuring quality: a cornerstone of theory in software engineering
In any engineering domain, a detailed understanding
of what constitutes a 'good' product is vital for
the development of theories that are both general and useful.
However, software engineering researchers' understanding of
desirable product qualities is not yet fuUy mature, especiaUy
for continuously-evolving software systems. Inspired by two
historical examples, this paper calls for a discipline-wide effort
to precisely define the attributes and variables of software
product quality in a measurable way. We expect this effort will
lead to two major contributions. Firstly, the defined attributes
and variables should act as units in any general theory of
software engineering. Secondly, once instruments to measure
these attributes and variables are developed, systematic largescale
empirical studies of software product quality will become
much easier, eventually yielding a rich corpus of data which
should prove fertile for further theory building
AF-APL: Bridging principles & practices in agent oriented languages
For AOP (Agent Oriented Programming) to become a mature discipline, lessons must be learned from practical language implementations. We present AF-APL (AgentFactory- Agent Programming Language) as an Agent Oriented Programming Language that has matured with continued revisions and implementations, resulting in a language-which, although based on the more theoretical aspects of AO design- has incorporated many of the practical considerations of programming real world agents. We describe AF-APL informally, focusing on its experience driven features, such as commitment reasoning, a rich plan operator set, and an inherent asynchronous design. We present the default execution cycle for the AF-APL interpreter, looking in detail at the Commitment Management model. This model provides an agent with power to reason about its own actions, while maintaining basic constraints on computational tractability. In our development of the language, we learned many lessons that are not covered in the purer AO language definitions. Before concluding, we discuss a number of these lessons. 1