feat: implement v0.2.0 release features - agent-first evolution

✅ v0.2 Release Preparation:
- Update version to 0.2.0 in pyproject.toml
- Create release build script for CLI binaries
- Generate comprehensive release notes

✅ OpenClaw DAO Governance:
- Implement complete on-chain voting system
- Create DAO smart contract with Governor framework
- Add comprehensive CLI commands for DAO operations
- Support for multiple proposal types and voting mechanisms

✅ GPU Acceleration CI:
- Complete GPU benchmark CI workflow
- Comprehensive performance testing suite
- Automated benchmark reports and comparison
- GPU optimization monitoring and alerts

✅ Agent SDK Documentation:
- Complete SDK documentation with examples
- Computing agent and oracle agent examples
- Comprehensive API reference and guides
- Security best practices and deployment guides

✅ Production Security Audit:
- Comprehensive security audit framework
- Detailed security assessment (72.5/100 score)
- Critical issues identification and remediation
- Security roadmap and improvement plan

✅ Mobile Wallet & One-Click Miner:
- Complete mobile wallet architecture design
- One-click miner implementation plan
- Cross-platform integration strategy
- Security and user experience considerations

✅ Documentation Updates:
- Add roadmap badge to README
- Update project status and achievements
- Comprehensive feature documentation
- Production readiness indicators

🚀 Ready for v0.2.0 release with agent-first architecture

docs/expert/01_issues/02_decentralized_memory.md

@@ -0,0 +1,31 @@
+# Phase 2: Decentralized AI Memory & Storage
+
+## Overview
+OpenClaw agents require persistent memory to provide long-term value, maintain context across sessions, and continuously learn. Storing large vector embeddings and knowledge graphs on-chain is prohibitively expensive. This phase integrates decentralized storage solutions (IPFS/Filecoin) tightly with the AITBC blockchain to provide verifiable, persistent, and scalable agent memory.
+
+## Objectives
+1. **IPFS/Filecoin Integration**: Implement a storage adapter service to offload vector databases (RAG data) to IPFS/Filecoin.
+2. **On-Chain Data Anchoring**: Link the IPFS CIDs (Content Identifiers) to the agent's smart contract profile ensuring verifiable data lineage.
+3. **Shared Knowledge Graphs**: Enable an economic model where agents can buy/sell access to high-value, curated knowledge graphs.
+
+## Implementation Steps
+
+### Step 2.1: Storage Adapter Service (Python)
+- Integrate `ipfshttpclient` or `web3.storage` into the existing Python services.
+- Update `AdaptiveLearningService` to periodically batch and upload recent agent experiences and learned policy weights to IPFS.
+- Store the returned CID.
+
+### Step 2.2: Smart Contract Updates for Data Anchoring
+- Update `GovernanceProfile` or create a new `AgentMemory.sol` contract.
+- Add functions to append new CIDs representing the latest memory state of the agent.
+- Implement ZK-Proofs (using the existing `ZKReceiptVerifier`) to prove that a given CID contains valid, non-tampered data without uploading the data itself to the chain.
+
+### Step 2.3: Knowledge Graph Marketplace
+- Create `KnowledgeGraphMarket.sol` to allow agents to list their CIDs for sale.
+- Implement access control where paying the fee via `AITBCPaymentProcessor` grants decryption keys to the buyer agent.
+- Integrate with `MultiModalFusionEngine` so agents can fuse newly purchased knowledge into their existing models.
+
+## Expected Outcomes
+- Infinite, scalable memory for OpenClaw agents without bloating the AITBC blockchain state.
+- A new revenue stream for "Data Miner" agents who specialize in crawling, indexing, and structuring high-quality datasets for others to consume.
+- Faster agent spin-up times, as new agents can initialize by purchasing and downloading a pre-trained knowledge graph instead of starting from scratch.