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Given the complexity of the topic, please note that these simplified markdown documents are quite abstract and high level. They can be used as a starting point for further detailed design and implementation:
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### Document 1: Hierarchical Swarms
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#### Overall Architecture
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1. Leader Agent (LA): This agent has the authority to manage and distribute tasks to the Worker Agents (WA).
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2. Worker Agents (WAs): These agents perform the tasks assigned by the LA.
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#### Simplified Requirements
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1. LA should be able to distribute tasks to WAs.
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2. WAs should be able to execute tasks and return results to LA.
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3. LA should be able to consolidate and process results.
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#### Pseudocode
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```
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create LA
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create WAs
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for each task in tasks:
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LA.distribute_task(WAs, task)
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for each WA in WAs:
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WA.execute_task()
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LA.collect_results(WAs)
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LA.process_results()
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```
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#### General Classes
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```python
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class LeaderAgent:
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def distribute_task(self, WAs, task):
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pass
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def collect_results(self, WAs):
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pass
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def process_results(self):
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pass
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class WorkerAgent:
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def execute_task(self):
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pass
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```
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### Document 2: Collaborative Swarms
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#### Overall Architecture
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1. Collaborative Agents (CAs): These agents work in parallel on different aspects of a task and then collectively determine the best output.
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#### Simplified Requirements
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1. CAs should be able to work on tasks in parallel.
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2. CAs should be able to collaborate to determine the best result.
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#### Pseudocode
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```
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create CAs
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for each task in tasks:
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for each CA in CAs:
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CA.execute_task(task)
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CA.collaborate()
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```
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#### General Classes
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```python
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class CollaborativeAgent:
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def execute_task(self, task):
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pass
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def collaborate(self):
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pass
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```
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### Document 3: Competitive Swarms
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#### Overall Architecture
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1. Competitive Agents (CompAs): These agents work independently on the same tasks, and the best result is selected.
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#### Simplified Requirements
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1. CompAs should be able to work independently on tasks.
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2. An evaluation method should be used to select the best result.
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#### Pseudocode
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```
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create CompAs
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for each task in tasks:
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for each CompA in CompAs:
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CompA.execute_task(task)
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evaluate_results(CompAs)
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```
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#### General Classes
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```python
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class CompetitiveAgent:
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def execute_task(self, task):
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pass
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def evaluate_results(CompAs):
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pass
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```
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Note: In the real world, the complexity of the architecture and requirements will significantly exceed what is presented here. These examples provide a basic starting point but should be expanded upon based on the specifics of the task or problem you're trying to solve.
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@ -0,0 +1,49 @@
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from abc import ABC, abstractmethod
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class LeaderAgent(ABC):
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@abstractmethod
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def distribute_task(self, WAs, task):
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pass
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@abstractmethod
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def collect_results(self, WAs):
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pass
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@abstractmethod
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def process_results(self):
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pass
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class WorkerAgent(ABC):
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@abstractmethod
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def execute_task(self):
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pass
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class CollaborativeAgent(ABC):
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@abstractmethod
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def execute_task(self, task):
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pass
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@abstractmethod
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def collaborate(self):
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pass
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class CompetitiveAgent(ABC):
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@abstractmethod
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def execute_task(self, task):
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pass
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def evaluate_results(CompAs):
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pass
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# Example
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class MyWorkerAgent(WorkerAgent):
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def execute_task(self):
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# Insert your implementation here
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pass
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