| 1. |
- Morales, Hernan E., et al.
(författare)
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Neutral and selective drivers of colour evolution in a widespread Australian passerine
- 2017
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Ingår i: Journal of Biogeography. - : WILEY-BLACKWELL. - 0305-0270 .- 1365-2699. ; 44:3, s. 522-536
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Tidskriftsartikel (refereegranskat)abstract
- AimRump plumage coloration of the Eastern Yellow Robin (Eopsaltria australis), a widespread Australian songbird, varies from bright yellow in the tropical north to olive-green in the temperate south. Here, we test whether colour variation: (1) correlates most strongly with neutral genetic variation and so is best explained by historical processes, (2) reflects selection associated with different visual environments (dense versus open habitats) and/or (3) reflects selection associated with climatic variation. LocationEastern Australia. MethodsWe quantified colour variation using reflectance spectrometry and visual models. We performed geographical cline analysis of colour and neutral genetic variation (genome-wide single nucleotide polymorphisms). We tested for correlations of colour variation with climate, vegetation density, geographical location and genetic variation. We accounted for covariation and spatial autocorrelation, and conducted analyses at continental and regional spatial scales. ResultsClinal variation of colour traits and neutral genetic markers were largely concordant. At the continental scale, colour variation was strongly associated with neutral genetic structure and geography, and to a lesser extent with environment. At the regional scale, environmental variation was a better predictor of colour variation than it was at the larger scale. Main conclusionAt the continental scale, colour variation is strongly associated with large-scale population history. In contrast, at the regional scale, where the influence of history and geography is weaker, environmental variation has a role in facilitating the maintenance of colour variation. Our results highlight the need to assess selective and neutral alternatives at multiple spatial scales when studying geographical variation.
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| 2. |
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| 3. |
- Strannegård, Claes, 1962, et al.
(författare)
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AI Tool for Exploring How Economic Activities Impact Local Ecosystems
- 2024
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Ingår i: Lecture Notes in Networks and Systems. - 2367-3389 .- 2367-3370. ; 825, s. 690-709
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Konferensbidrag (refereegranskat)abstract
- We present an AI-based ecosystem simulator that uses three-dimensional models of the terrain and animal models controlled by deep reinforcement learning. The simulations take place in a game engine environment, which enables continuous visual observation of the ecosystem model. The terrain models are generated from geographic data with altitudes and land cover type. The animal models combine three-dimensional conformation models with animation schemes and decision-making mechanisms trained with deep reinforcement learning in increasingly complex environments (curriculum learning). We show how AI tools of this kind can be used for modeling the development of specific ecosystems with and without different forms of economic activities. In particular, we show how they might be used for modeling local biodiversity effects of land cover change, exploitation of natural resources, pollution, invasive species, and climate change.
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| 4. |
- Strannegård, Claes, 1962, et al.
(författare)
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Combining Evolution and Learning in Computational Ecosystems
- 2020
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Ingår i: Journal of Artificial Intelligence. - : Walter de Gruyter GmbH. - 1994-5450 .- 1946-0163. ; 11:1, s. 1-37
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Tidskriftsartikel (refereegranskat)abstract
- Although animals such as spiders, fish, and birds have very different anatomies, the basic mechanisms that govern their perception, decision-making, learning, reproduction, and death have striking similarities. These mechanisms have apparently allowed the development of general intelligence in nature. This led us to the idea of approaching artificial general intelligence (AGI) by constructing a generic artificial animal (animat) with a configurable body and fixed mechanisms of perception, decision-making, learning, reproduction, and death. One instance of this generic animat could be an artificial spider, another an artificial fish, and a third an artificial bird. The goal of all decision-making in this model is to maintain homeostasis. Thus actions are selected that might promote survival and reproduction to varying degrees. All decision-making is based on knowledge that is stored in network structures. Each animat has two such network structures: a genotype and a phenotype. The genotype models the initial nervous system that is encoded in the genome (“the brain at birth”), while the phenotype represents the nervous system in its present form (“the brain at present”). Initially the phenotype and the genotype coincide, but then the phenotype keeps developing as a result of learning, while the genotype essentially remains unchanged. The model is extended to ecosystems populated by animats that develop continuously according to fixed mechanisms for sexual or asexual reproduction, and death. Several examples of simple ecosystems are given. We show that our generic animat model possesses general intelligence in a primitive form. In fact, it can learn simple forms of locomotion, navigation, foraging, language, and arithmetic.
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| 5. |
- Strannegård, Claes, 1962, et al.
(författare)
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Ecosystem Models Based on Artificial Intelligence
- 2022
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Ingår i: 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- Ecosystem models can be used for understanding general phenomena of evolution, ecology, and ethology. They can also be used for analyzing and predicting the ecological consequences of human activities on specific ecosystems, e.g., the effects of agriculture, forestry, construction, hunting, and fishing. We argue that powerful ecosystem models need to include reasonable models of the physical environment and of animal behavior. We also argue that several well-known ecosystem models are unsatisfactory in this regard. Then we present the open-source ecosystem simulator Ecotwin, which is built on top of the game engine Unity. To model a specific ecosystem in Ecotwin, we first generate a 3D Unity model of the physical environment, based on topographic or bathymetric data. Then we insert digital 3D models of the organisms of interest into the environment model. Each organism is equipped with a genome and capable of sexual or asexual reproduction. An organism dies if it runs out of some vital resource or reaches its maximum age. The animal models are equipped with behavioral models that include sensors, actions, reward signals, and mechanisms of learning and decision-making. Finally, we illustrate how Ecotwin works by building and running one terrestrial and one marine ecosystem model.
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| 6. |
- Strannegård, Claes, 1962, et al.
(författare)
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Evolution and learning in artificial ecosystems
- 2018
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Ingår i: In Proceedings of IJCAI-18 Workshop on Architectures for Generality and Autonomy, 2018.
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Konferensbidrag (refereegranskat)abstract
- A generic model is presented for ecosystems inhabited by artificial animals, or animats, that develop over time. The individual animats develop continuously by means of generic mechanisms for learning, forgetting, and decisionmaking. At the same time, the animat populations develop in an evolutionary process based on fixed mechanisms for sexual and asexual reproduction, mutation, and death. The animats of the ecosystems move, eat, learn, make decisions, interact with other animats, reproduce, and die. Each animat has its individual sets of homeostatic variables, sensors, and motors. It also has its own memory graph that forms the basis of its decision-making. This memory graph has an architecture (i.e. graph topology) that changes over time via mechanisms for adding and removing nodes. Our approach combines genetic algorithms, reinforcement learning, homeostatic decision-making, and dynamic concept formation. To illustrate the generality of the model, five examples of ecosystems are given, ranging from a simple world inhabited by a single frog to a more complex world in which grass, sheep, and wolves interact.
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| 7. |
- Strannegård, Claes, 1962, et al.
(författare)
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Survival games for humans and machines
- 2024
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Ingår i: COGNITIVE SYSTEMS RESEARCH. - 2214-4366 .- 1389-0417. ; 86
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Tidskriftsartikel (refereegranskat)abstract
- Survival games can be described as video games where the player searches for food and treasures, while avoiding obstacles and hostile attacks. Ms.Pac-Man and Minecraft are two well-known examples. Currently there are AI models that outperform human players at Ms.Pac-Man, while AI models playing Minecraft above the human level has been a long-standing challenge. This paper concerns what we call pure survival games, which take place in previously unseen worlds containing only food, water, and obstacles. The challenge of the player is to navigate and survive in those worlds by continuously finding resources and avoiding obstacles. Arguably, animals need to master physical analogues of pure survival games in order to survive and reproduce. Here we begin to explore human and machine performance on pure survival games. We define two games called the Grid game and the Terrain game and two corresponding AI agents based on deep reinforcement learning: the Grid agent and the Terrain agent. We explore to what extent these agents can match human performance and how their performance is affected by variations in their perception, memory, and reward models. We find that (1) the Terrain agent performs above human level, while the Grid agent performs below human level; (2) the smell, touch, and interoception models contribute significantly to the performance of the Grid agent; (3) the memory model contributes significantly to the performance of the Grid agent; and (4) the performance of the Grid agent is relatively stable under three quite different reward signals, including one that rewards survival and nothing else.
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| 8. |
- Svensson, P. Andreas, 1973-, et al.
(författare)
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Experimentally induced divergence of carotenoid usage in male guppy ornaments
- 2014
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Konferensbidrag (refereegranskat)abstract
- Females are often believed to use male ornaments as observable indicators of non-observable male traits. However, if signal form (e.g. coloration) is highly flexible, its link to signal content (e.g. quality) should be unreliable. Therefore, it is often implicitly assumed that signals are heavily constrained and relatively stable over generations. One popular illustration of costly ornaments is carotenoid-based colour signals. Recent but indirect evidence suggest that such signals may in fact evolve rapidly, but this has not been tested experimentally. We exposed large replicated populations of guppies (Poecilia reticulata; effective population sizes >1000) to three environmental conditions in a multi-generation experiment. The treatments differed in the spectral composition of ambient light by using colour filters which affected how male colours were percieved. This, in turn, was expected to lead to male coloration divergence between treatments due to female choice. In addition, the filters affected the micro-flora and -fauna, which are dietary sources of ornamental pigments. Male skin carotenoids were analysed after 3 and 5 generations. In this short time, populations had diverged in male coloration and in the carotenoid composition of sexual ornaments. A second experiment disentangled environmental and genetic effects. Our study demonstrates evolutionary innovation in signal traits, and how dietary-driven responses to environmental change can impact sexual ornaments.
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| 9. |
- Svensson, P. Andreas, 1973-, et al.
(författare)
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Quantifying ornamental carotenoids in male guppies, Poecilia reticulata
- 2012
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Ingår i: 5th International Conference of Poeciliid Biologists (Trinidad and Tobago).
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Konferensbidrag (refereegranskat)abstract
- For over 30 years, the orange spots of male guppies have been an iconic example of carotenoid-based ornamentation. The humble guppy was the first of many model species used to study carotenoids in sexual coloration and it is a favoured text book example of signal evolution. It is therefore rather surprising that few have attempted to identify and quantify the carotenoids present in guppies. With some exceptions (most notably Greg Grether's work), researchers have instead tried to infer pigment concentration from colorimetric techniques such as reflectance spectrophotometry or photography. Three major obstacles exist for accurate biochemical determination the carotenoids present in guppies. First, the small body size means that only miniscule amounts are available for analysis. Second, fish skin carotenoids are esterified and samples therefore require potentially destructive hydrolysis. Third, some of the carotenoids are structurally similar, which poses a challenge for successful separation. We have developed a method to identify and quantify the individual carotenoids in guppy skin by using mild saponifiction followed by normal phase high performance liquid chromatography (NP-HPLC). It provides effective hydrolysis of the carotenoid esters without damage to the pigments and is sensitive enough to quantify the carotenoids in a single skin spot. We also used different photographic techniques to measure coloration of both free-swimming and sedated male guppies to investigate how accurate photographic methods are in estimating carotenoid levels.
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