An investigation into XSets of primitive behaviours for emergent behaviour in stigmergic and message passing antlike agents
- Authors: Chibaya, Colin
- Date: 2014
- Subjects: Ants -- Behavior -- Computer programs , Insects -- Behavior -- Computer programs , Ant communities -- Behavior , Insect societies
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:4698 , http://hdl.handle.net/10962/d1012965
- Description: Ants are fascinating creatures - not so much because they are intelligent on their own, but because as a group they display compelling emergent behaviour (the extent to which one observes features in a swarm which cannot be traced back to the actions of swarm members). What does each swarm member do which allows deliberate engineering of emergent behaviour? We investigate the development of a language for programming swarms of ant agents towards desired emergent behaviour. Five aspects of stigmergic (pheromone sensitive computational devices in which a non-symbolic form of communication that is indirectly mediated via the environment arises) and message passing ant agents (computational devices which rely on implicit communication spaces in which direction vectors are shared one-on-one) are studied. First, we investigate the primitive behaviours which characterize ant agents' discrete actions at individual levels. Ten such primitive behaviours are identified as candidate building blocks of the ant agent language sought. We then study mechanisms in which primitive behaviours are put together into XSets (collection of primitive behaviours, parameter values, and meta information which spells out how and when primitive behaviours are used). Various permutations of XSets are possible which define the search space for best performer XSets for particular tasks. Genetic programming principles are proposed as a search strategy for best performer XSets that would allow particular emergent behaviour to occur. XSets in the search space are evolved over various genetic generations and tested for abilities to allow path finding (as proof of concept). XSets are ranked according to the indices of merit (fitness measures which indicate how well XSets allow particular emergent behaviour to occur) they achieve. Best performer XSets for the path finding task are identifed and reported. We validate the results yield when best performer XSets are used with regard to normality, correlation, similarities in variation, and similarities between mean performances over time. Commonly, the simulation results yield pass most statistical tests. The last aspect we study is the application of best performer XSets to different problem tasks. Five experiments are administered in this regard. The first experiment assesses XSets' abilities to allow multiple targets location (ant agents' abilities to locate continuous regions of targets), and found out that best performer XSets are problem independent. However both categories of XSets are sensitive to changes in agent density. We test the influences of individual primitive behaviours and the effects of the sequences of primitive behaviours to the indices of merit of XSets and found out that most primitive behaviours are indispensable, especially when specific sequences are prescribed. The effects of pheromone dissipation to the indices of merit of stigmergic XSets are also scrutinized. Precisely, dissipation is not causal. Rather, it enhances convergence. Overall, this work successfully identify the discrete primitive behaviours of stigmergic and message passing ant-like devices. It successfully put these primitive behaviours together into XSets which characterize a language for programming ant-like devices towards desired emergent behaviour. This XSets approach is a new ant language representation with which a wider domain of emergent tasks can be resolved.
- Full Text:
- Date Issued: 2014
- Authors: Chibaya, Colin
- Date: 2014
- Subjects: Ants -- Behavior -- Computer programs , Insects -- Behavior -- Computer programs , Ant communities -- Behavior , Insect societies
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:4698 , http://hdl.handle.net/10962/d1012965
- Description: Ants are fascinating creatures - not so much because they are intelligent on their own, but because as a group they display compelling emergent behaviour (the extent to which one observes features in a swarm which cannot be traced back to the actions of swarm members). What does each swarm member do which allows deliberate engineering of emergent behaviour? We investigate the development of a language for programming swarms of ant agents towards desired emergent behaviour. Five aspects of stigmergic (pheromone sensitive computational devices in which a non-symbolic form of communication that is indirectly mediated via the environment arises) and message passing ant agents (computational devices which rely on implicit communication spaces in which direction vectors are shared one-on-one) are studied. First, we investigate the primitive behaviours which characterize ant agents' discrete actions at individual levels. Ten such primitive behaviours are identified as candidate building blocks of the ant agent language sought. We then study mechanisms in which primitive behaviours are put together into XSets (collection of primitive behaviours, parameter values, and meta information which spells out how and when primitive behaviours are used). Various permutations of XSets are possible which define the search space for best performer XSets for particular tasks. Genetic programming principles are proposed as a search strategy for best performer XSets that would allow particular emergent behaviour to occur. XSets in the search space are evolved over various genetic generations and tested for abilities to allow path finding (as proof of concept). XSets are ranked according to the indices of merit (fitness measures which indicate how well XSets allow particular emergent behaviour to occur) they achieve. Best performer XSets for the path finding task are identifed and reported. We validate the results yield when best performer XSets are used with regard to normality, correlation, similarities in variation, and similarities between mean performances over time. Commonly, the simulation results yield pass most statistical tests. The last aspect we study is the application of best performer XSets to different problem tasks. Five experiments are administered in this regard. The first experiment assesses XSets' abilities to allow multiple targets location (ant agents' abilities to locate continuous regions of targets), and found out that best performer XSets are problem independent. However both categories of XSets are sensitive to changes in agent density. We test the influences of individual primitive behaviours and the effects of the sequences of primitive behaviours to the indices of merit of XSets and found out that most primitive behaviours are indispensable, especially when specific sequences are prescribed. The effects of pheromone dissipation to the indices of merit of stigmergic XSets are also scrutinized. Precisely, dissipation is not causal. Rather, it enhances convergence. Overall, this work successfully identify the discrete primitive behaviours of stigmergic and message passing ant-like devices. It successfully put these primitive behaviours together into XSets which characterize a language for programming ant-like devices towards desired emergent behaviour. This XSets approach is a new ant language representation with which a wider domain of emergent tasks can be resolved.
- Full Text:
- Date Issued: 2014
Flock inspired area coverage using wireless boid-like sensor agents
- Chibaya, Colin, Bangay, Shaun D
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2008
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433440 , vital:72970 , 10.1109/UKSIM.2008.102
- Description: Simulated flocking is achievable using three boid rules [13]. We propose an area coverage model inspired by Reynolds’ flocking algorithm, investigating strategies for achieving quality coverage using flocking rules. Our agents are identical and autonomous, using only local sensory information for indirect communication. Upon deployment, agents are in the default separation mode. The cohesion rule would then guarantee that agents remain within the swarm, covering spaces with explored neighbour spaces. Four experiments are conducted to evaluate our model in terms of coverage quality achieved. We firstly investigate agents’ separation speed before the speed with which isolated agents re-organizes is investigated. The third experiment compares coverage quality achieved using our model with coverage quality achieved using random guessing. Finally, we investigate fault tolerance in the event of agents’ failures. Our model exhibits good separation and cohesion speed, achieving high quality coverage. Additionally, the model is fault tolerant and adaptive to agents’ failures.
- Full Text:
- Date Issued: 2008
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2008
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433440 , vital:72970 , 10.1109/UKSIM.2008.102
- Description: Simulated flocking is achievable using three boid rules [13]. We propose an area coverage model inspired by Reynolds’ flocking algorithm, investigating strategies for achieving quality coverage using flocking rules. Our agents are identical and autonomous, using only local sensory information for indirect communication. Upon deployment, agents are in the default separation mode. The cohesion rule would then guarantee that agents remain within the swarm, covering spaces with explored neighbour spaces. Four experiments are conducted to evaluate our model in terms of coverage quality achieved. We firstly investigate agents’ separation speed before the speed with which isolated agents re-organizes is investigated. The third experiment compares coverage quality achieved using our model with coverage quality achieved using random guessing. Finally, we investigate fault tolerance in the event of agents’ failures. Our model exhibits good separation and cohesion speed, achieving high quality coverage. Additionally, the model is fault tolerant and adaptive to agents’ failures.
- Full Text:
- Date Issued: 2008
The relationship between emergence of the shortest path and information value using ant-like agents
- Chibaya, Colin, Bangay, Shaun D
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2008
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433318 , vital:72961 , https://doi.org/10.1145/1456659.1456663
- Description: Ant-like agents forage between two points. These agents' probabilistic movements are based on the use of two pheromones; one marking trails towards the goal and another marking trails back to the starting point. Path selection decisions are influenced by the relative levels of attractive and repulsive pheromone in each agent's local environment. Our work in [5] evaluates three pheromone perception strategies, investigating path formation speed, quality, directionality, robustness and adaptability under different parameter settings(degree of randomness, pheromone evaporation rate and pheromone diffusion rate).
- Full Text:
- Date Issued: 2008
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2008
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433318 , vital:72961 , https://doi.org/10.1145/1456659.1456663
- Description: Ant-like agents forage between two points. These agents' probabilistic movements are based on the use of two pheromones; one marking trails towards the goal and another marking trails back to the starting point. Path selection decisions are influenced by the relative levels of attractive and repulsive pheromone in each agent's local environment. Our work in [5] evaluates three pheromone perception strategies, investigating path formation speed, quality, directionality, robustness and adaptability under different parameter settings(degree of randomness, pheromone evaporation rate and pheromone diffusion rate).
- Full Text:
- Date Issued: 2008
A probabilistic movement model for shortest path formation in virtual ant-like agents
- Chibaya, Colin, Bangay, Shaun D
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2007
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433125 , vital:72945 , https://doi.org/10.1145/1292491.1292493
- Description: We propose a probabilistic movement model for controlling ant-like agents foraging between two points. Such agents are all identical, simple, autonomous and can only communicate indirectly through the environment. These agents secrete two types of pheromone, one to mark trails towards the goal and another to mark trails back to the starting point. Three pheromone perception strategies are proposed (Strategy A, B and C). Agents that use strategy A perceive the desirability of a neighbouring location as the difference between levels of attractive and repulsive pheromone in that location. With strategy B, agents perceive the desirability of a location as the quotient of levels of attractive and repulsive pheromone. Agents using strategy C determine the product of the levels of attractive pheromone with the complement of levels of repulsive pheromone. We conduct experiments to confirm directionality as emergent property of trails formed by agents that use each strategy. In addition, we compare path formation speed and the quality of the formed path under changes in the environment. We also investigate each strategy's robustness in environments that contain obstacles. Finally, we investigate how adaptive each strategy is when obstacles are eventually removed from the scene and find that the best strategy of these three is strategy A. Such a strategy provides useful guidelines to researchers in further applications of swarm intelligence metaphors for complex problem solving.
- Full Text:
- Date Issued: 2007
- Authors: Chibaya, Colin , Bangay, Shaun D
- Date: 2007
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/433125 , vital:72945 , https://doi.org/10.1145/1292491.1292493
- Description: We propose a probabilistic movement model for controlling ant-like agents foraging between two points. Such agents are all identical, simple, autonomous and can only communicate indirectly through the environment. These agents secrete two types of pheromone, one to mark trails towards the goal and another to mark trails back to the starting point. Three pheromone perception strategies are proposed (Strategy A, B and C). Agents that use strategy A perceive the desirability of a neighbouring location as the difference between levels of attractive and repulsive pheromone in that location. With strategy B, agents perceive the desirability of a location as the quotient of levels of attractive and repulsive pheromone. Agents using strategy C determine the product of the levels of attractive pheromone with the complement of levels of repulsive pheromone. We conduct experiments to confirm directionality as emergent property of trails formed by agents that use each strategy. In addition, we compare path formation speed and the quality of the formed path under changes in the environment. We also investigate each strategy's robustness in environments that contain obstacles. Finally, we investigate how adaptive each strategy is when obstacles are eventually removed from the scene and find that the best strategy of these three is strategy A. Such a strategy provides useful guidelines to researchers in further applications of swarm intelligence metaphors for complex problem solving.
- Full Text:
- Date Issued: 2007
- «
- ‹
- 1
- ›
- »