Herbert　Simon　(1916.6.15　-　2001.2.9)　was　one　of　the　greatest　pioneers　in　cognitive　science　and　artificial　intelligence,　as　well　as　in　behavior　economics　and　many　other　fields.　Problem　solving　was　his　core　work　in　artificial　intelligence　and　cognitive　psychology.　He　and　Newell　first　postulated　a　general　and　systematic　framework　of　human　(and　machine)　problem　solving　as　iteratively　applying　operators　to　transform　the　state　of　the　problem　from　the　starting　state　in　problem　state　space　to　eventually　achieve　the　goal　state.　Heuristic　problem　solving　includes　two　basic　components:　heuristic　searching　(such　as　means-ends　analysis)　and　heuristic　rules　(used　to　change　the　problem　states).　And　then,　he　extended　this　framework　in　two　dimensions.　One　is　applying　this　framework　to　creative　learning　and　scientific　discovery　(both　were　thought　as　specific　ill-structured　problem　solving　tasks);　the　other　is　to　elaborate　this　general　framework　with　more　detailed　models　in　memory　(such　as　chunk　structure　in　short　term　memory)　and　the　knowledge　(and　problem)　representations,　including　the　knowledge　structure　difference　between　experts　and　naives,　diagrammatic　representation　and　mental　imagery.　To　meet　the　challenge　of　Web　intelligence　and　to　pioneer　the　effective　and　efficient　ways　of　information　processing　at　Web　scale,　as　the　first　step,　we　would　learn　this　process　from　human　brain,　one　of　the　greatest　webs,　based　on　Simon　and　Newell’s　framework　in　problem　solving.　We　have　found　that,　even　in　the　basic　application　of　heuristic　rules,　the　processes　are　distributed　in　several　major　parts　of　brain　and　with　certain　areas　for　the　communications　across　these　networks.　We　have　checked　the　brain　activations　in　regard　to　working　memory　and　mental　imagery　in　problem　solving.　We　have　also　found　the　evidences　supporting　the　hypothesis　that　the　scientific　discovery　is　a　specific　problem　solving　from　neural　activations　that　central　brain　areas　activated　in　scientific　discovery　overlapping　with　the　areas　in　general　problem　solving　tasks.　These　findings　offer　strong　clues　for　how　to　solve　problems　at　Web　scale.　©　Springer-Verlag　Berlin　Heidelberg　2011.